Every evidence row now records its derivation (direct, assertion, operator, external, prediction, consolidation, inference, reflection, dream, retrieval), its independent-source family (an actor, an integration, an operator, a prediction) and its root event or memory ids. Confidence groups evidence by family: the strongest primary item counts in full, each further primary item adds a quarter, capped at 1.5x, and derived items count only when the family has no primary member. Three derived re-expressions of one utterance therefore weigh exactly what the utterance weighs, while three independent families still add up. Producers (conversation, association, consolidation, predictions, metacognition, dreaming, operator and seed input, contradictions) supply their ancestry. Existing rows are marked legacy_unknown with family = source; nothing is invented. The belief page shows per-family contributions and the replay test checks that provenance is reconstructed identically in the sandbox. Migration 0017 is additive.
399 lines
13 KiB
Go
399 lines
13 KiB
Go
// Package beliefs manages propositions held with explicit, evidence-derived
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// confidence. Confidence is arithmetic over evidence weights and source
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// credibility; no model ever sets it directly (spec §10, §62).
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package beliefs
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import (
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"encoding/json"
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"math"
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"sort"
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"strings"
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"github.com/andydixon/noema/pkg/concepts"
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"github.com/andydixon/noema/pkg/events"
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)
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// Status of a belief.
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type Status string
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// Statuses in rough order of commitment.
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const (
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StatusHypothesis Status = "hypothesis"
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StatusTentative Status = "tentative"
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StatusLikely Status = "likely"
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StatusAccepted Status = "accepted"
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StatusContested Status = "contested"
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StatusRejected Status = "rejected"
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StatusSuperseded Status = "superseded"
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)
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// Valid reports whether s is known.
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func (s Status) Valid() bool {
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switch s {
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case StatusHypothesis, StatusTentative, StatusLikely, StatusAccepted, StatusContested, StatusRejected, StatusSuperseded:
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return true
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}
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return false
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}
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// Slope converts net evidence into log-odds. 1.5 means one unit of fully
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// credible evidence moves 0.5 to about 0.82.
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const Slope = 1.5
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// Bounds keep beliefs away from certainty unless an operator pins a fact.
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const (
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MinConfidence = 0.02
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MaxConfidence = 0.98
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)
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// PriorFor returns the starting confidence for an epistemic kind.
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func PriorFor(e concepts.Epistemic) float64 {
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switch e {
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case concepts.Hypothesis, concepts.Inference:
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return 0.25
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case concepts.Assumption, concepts.Opinion:
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return 0.4
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case concepts.Claim:
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return 0.5
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case concepts.Observation, concepts.Memory:
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return 0.6
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case concepts.Fact:
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return 0.8
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default:
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return 0.5
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}
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}
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// Evidence is one piece of support or opposition.
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type Evidence struct {
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Direction string `json:"direction"` // for | against
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Kind string `json:"kind"`
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RefID string `json:"ref_id"`
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Source string `json:"source"`
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Weight float64 `json:"weight"` // how strongly it bears on the proposition, (0,1]
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Credibility float64 `json:"credibility"` // trust in the source, [0,1]
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Retracted bool `json:"retracted"`
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// Provenance. Family is the independent-source key (an actor, an
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// integration, an operator); Derivation says how this row relates to its
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// roots; RootIDs are the originating event or memory ids. Derived rows
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// (consolidation, inference, reflection, dream, retrieval) never add
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// weight to a family that already has a primary member: they carry no
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// information their roots did not.
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Derivation string `json:"derivation,omitempty"`
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Family string `json:"family,omitempty"`
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RootIDs []string `json:"root_ids,omitempty"`
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ProvenanceStatus string `json:"provenance_status,omitempty"` // recorded | legacy_unknown
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}
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// Derivations. Primary derivations bring information from outside the
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// belief system; derived ones re-express information already present.
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const (
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DerivationDirect = "direct" // an observation or event from the source itself
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DerivationAssertion = "assertion" // somebody stated the proposition
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DerivationOperator = "operator" // an operator asserted or endorsed it
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DerivationExternal = "external" // external corroboration (integration, tool result)
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DerivationPrediction = "prediction" // a prediction resolved against events
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DerivationConsolidation = "consolidation" // generalised from episodes
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DerivationInference = "inference" // reasoned from other items
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DerivationReflection = "reflection" // produced by reflection or metacognition
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DerivationDream = "dream" // proposed while dreaming
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DerivationRetrieval = "retrieval" // a recalled memory offered as support
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DerivationLegacy = "legacy" // written before provenance existed; treated as primary
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)
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// Derived reports whether a derivation re-expresses existing information.
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func Derived(d string) bool {
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switch d {
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case DerivationConsolidation, DerivationInference, DerivationReflection, DerivationDream, DerivationRetrieval:
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return true
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}
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return false
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}
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// FamilyOf returns the grouping key for a piece of evidence: its recorded
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// family, else its source, else its reference.
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func FamilyOf(e Evidence) string {
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if e.Family != "" {
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return e.Family
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}
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if e.Source != "" {
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return e.Source
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}
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return e.Kind + ":" + e.RefID
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}
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// FamilyForActor is the family key for statements made by a person or agent.
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func FamilyForActor(actor string) string {
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actor = strings.ToLower(strings.TrimSpace(actor))
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if actor == "" {
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return ""
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}
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return "actor:" + actor
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}
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// FamilyForSource is the family key for an integration or channel that has
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// no individual actor (metrics, webhooks, repositories).
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func FamilyForSource(source, channel string) string {
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source = strings.ToLower(strings.TrimSpace(source))
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if source == "" {
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return ""
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}
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if channel = strings.ToLower(strings.TrimSpace(channel)); channel != "" {
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return "source:" + source + ":" + channel
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}
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return "source:" + source
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}
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// FamilyFromEvent derives the family of an observation from its payload:
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// the actor who spoke, else the integration or channel it came from, else
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// the event's source component.
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func FamilyFromEvent(ev events.Event) string {
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var p events.ObservationPayload
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if len(ev.Payload) > 0 {
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json.Unmarshal(ev.Payload, &p) //nolint:errcheck // absent payload fields simply fall through
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}
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if f := FamilyForActor(p.Actor); f != "" {
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return f
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}
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if f := FamilyForSource(p.Source, p.Channel); f != "" {
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return f
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}
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return FamilyForSource(ev.Source, "")
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}
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// FamilyShare explains one family's contribution to a confidence.
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type FamilyShare struct {
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Family string `json:"family"`
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Direction string `json:"direction"`
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Items int `json:"items"`
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Primary int `json:"primary"`
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Contribution float64 `json:"contribution"`
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}
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// Breakdown explains a confidence value.
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type Breakdown struct {
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Prior float64 `json:"prior"`
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Families []FamilyShare `json:"families,omitempty"` // per independent-source group
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For float64 `json:"for"` // Σ weight×credibility, supporting
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Against float64 `json:"against"` // Σ weight×credibility, opposing
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SourcesFor int `json:"sources_for"` // distinct sources supporting
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DiversityScale float64 `json:"diversity_scale"` // discount when support comes from one source
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LogOdds float64 `json:"log_odds"`
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Confidence float64 `json:"confidence"`
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Formula string `json:"formula"`
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Notes []string `json:"notes,omitempty"`
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}
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// Compute derives confidence from prior and evidence.
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//
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// Evidence is grouped by family (independent source). Within a family the
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// strongest primary item counts in full and each further primary item adds
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// a quarter of its value, capped at one and a half times the strongest, so
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// repetition from one source is worth little. Derived items (consolidation,
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// inference, reflection, dream, retrieval) contribute only when their family
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// has no primary item, and then only the strongest of them: a semantic
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// memory consolidated from five episodes, and an inference drawn from it,
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// re-express the episodes rather than corroborate them. Diversity counts
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// families, not rows (T4: poisoned memory; review pass item 2).
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func Compute(prior float64, ev []Evidence) Breakdown {
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b := Breakdown{Prior: clampP(prior), Formula: "confidence = sigmoid(logit(prior) + slope × (for × diversity − against)); for/against sum per-family contributions (strongest primary + ¼ of the rest, capped at 1.5×; derived items only when no primary exists)"}
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type group struct {
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primary, derived []float64
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items int
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}
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groups := map[string]map[string]*group{"for": {}, "against": {}}
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var order []string
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for _, e := range ev {
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if e.Retracted || e.Weight <= 0 {
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continue
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}
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v := clamp01(e.Weight) * clamp01(e.Credibility)
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dir := "for"
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if e.Direction == "against" {
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dir = "against"
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}
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fam := FamilyOf(e)
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g := groups[dir][fam]
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if g == nil {
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g = &group{}
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groups[dir][fam] = g
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order = append(order, dir+"\x00"+fam)
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}
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g.items++
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if Derived(e.Derivation) {
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g.derived = append(g.derived, v)
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} else {
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g.primary = append(g.primary, v)
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}
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}
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contribution := func(g *group) float64 {
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if len(g.primary) > 0 {
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sort.Sort(sort.Reverse(sort.Float64Slice(g.primary)))
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c := g.primary[0]
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for _, v := range g.primary[1:] {
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c += 0.25 * v
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}
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return math.Min(c, 1.5*g.primary[0])
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}
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best := 0.0
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for _, v := range g.derived {
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best = math.Max(best, v)
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}
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return best
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}
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for _, key := range order {
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dir, fam, _ := strings.Cut(key, "\x00")
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g := groups[dir][fam]
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c := contribution(g)
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b.Families = append(b.Families, FamilyShare{Family: fam, Direction: dir, Items: g.items, Primary: len(g.primary), Contribution: round4(c)})
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if dir == "against" {
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b.Against += c
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continue
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}
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b.For += c
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}
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b.SourcesFor = len(groups["for"])
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// One source: 60% of face value; three or more independent sources: full.
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b.DiversityScale = 1
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if b.SourcesFor > 0 {
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b.DiversityScale = round4(0.6 + 0.4*math.Min(1, float64(b.SourcesFor-1)/2))
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}
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if b.SourcesFor == 1 && b.For > 0 {
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b.Notes = append(b.Notes, "all support comes from a single source")
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}
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logit := math.Log(b.Prior / (1 - b.Prior))
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b.LogOdds = logit + Slope*(b.For*b.DiversityScale-b.Against)
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b.Confidence = clampP(1 / (1 + math.Exp(-b.LogOdds)))
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b.For, b.Against, b.LogOdds, b.Confidence = round4(b.For), round4(b.Against), round4(b.LogOdds), round4(b.Confidence)
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return b
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}
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// Derive maps a breakdown to a status. Contested requires real evidence on
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// both sides; rejected requires the evidence to have pushed confidence low.
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func Derive(b Breakdown, epistemic concepts.Epistemic) Status {
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if b.For > 0 && b.Against > 0 && b.Against >= 0.5*b.For*b.DiversityScale && b.Confidence >= 0.2 && b.Confidence <= 0.8 {
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return StatusContested
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}
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switch {
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case b.Confidence < 0.15:
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return StatusRejected
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case b.For == 0 && epistemic == concepts.Hypothesis:
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return StatusHypothesis
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case b.Confidence < 0.5:
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if epistemic == concepts.Hypothesis {
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return StatusHypothesis
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}
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return StatusTentative
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case b.Confidence < 0.7:
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return StatusTentative
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case b.Confidence < 0.85:
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return StatusLikely
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default:
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return StatusAccepted
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}
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}
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func clampP(v float64) float64 {
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if math.IsNaN(v) || v < MinConfidence {
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return MinConfidence
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}
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if v > MaxConfidence {
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return MaxConfidence
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}
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return v
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}
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func clamp01(v float64) float64 {
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if math.IsNaN(v) || v < 0 {
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return 0
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}
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if v > 1 {
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return 1
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}
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return v
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}
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func round4(v float64) float64 { return math.Round(v*10000) / 10000 }
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// negations are the words that flip a proposition's polarity for the
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// deterministic contradiction check.
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var negations = map[string]bool{"not": true, "no": true, "never": true, "isn't": true, "isnt": true, "doesn't": true, "doesnt": true, "don't": true, "dont": true, "cannot": true, "can't": true, "cant": true, "wasn't": true, "didn't": true, "won't": true, "unlikely": true, "false": true}
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// Polarity splits a proposition into its content tokens and whether it is negated.
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func Polarity(text string) (tokens []string, negated bool) {
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for _, w := range tokenise(text) {
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if negations[w] {
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negated = !negated
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continue
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}
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tokens = append(tokens, w)
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}
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sort.Strings(tokens)
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return tokens, negated
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}
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// Jaccard similarity of two token lists.
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func Jaccard(a, b []string) float64 {
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if len(a) == 0 || len(b) == 0 {
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return 0
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}
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set := map[string]bool{}
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for _, w := range a {
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set[w] = true
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}
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inter := 0
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seenB := map[string]bool{}
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for _, w := range b {
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if seenB[w] {
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continue
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}
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seenB[w] = true
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if set[w] {
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inter++
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}
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}
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union := len(set) + len(seenB) - inter
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return float64(inter) / float64(union)
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}
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// Contradicts reports whether two propositions are the same content with
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// opposite polarity (deterministic first pass; paraphrase judgement can be
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// added by an LLM-assisted process later).
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func Contradicts(a, b string) (bool, float64) {
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ta, na := Polarity(a)
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tb, nb := Polarity(b)
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sim := Jaccard(ta, tb)
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if na != nb && sim >= 0.6 {
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return true, round4(sim)
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}
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return false, round4(sim)
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}
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var stop = map[string]bool{"the": true, "a": true, "an": true, "is": true, "are": true, "was": true, "were": true, "be": true, "been": true, "of": true, "to": true, "in": true, "on": true, "at": true, "for": true, "and": true, "or": true, "that": true, "this": true, "it": true, "has": true, "have": true, "had": true, "with": true, "by": true, "as": true, "may": true, "might": true, "probably": true, "likely": true}
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func tokenise(text string) []string {
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var out []string
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var cur []rune
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flush := func() {
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if len(cur) >= 2 {
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w := string(cur)
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if !stop[w] {
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out = append(out, w)
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}
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}
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cur = cur[:0]
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}
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for _, r := range text {
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switch {
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case r >= 'A' && r <= 'Z':
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cur = append(cur, r+32)
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case r >= 'a' && r <= 'z' || r >= '0' && r <= '9' || r == '\'' || r == '-' || r == '_' || r == '.':
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cur = append(cur, r)
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default:
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flush()
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}
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}
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flush()
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return out
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}
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