{"id":"b664c4c0-36e9-4e90-bfef-3bc9c2b910b3","workspace_slug":"orbital","window_days":7,"window_start":"2026-05-02T00:00:00Z","window_end":"2026-05-09T00:00:00Z","generated_at":"2026-05-08T22:10:14.251365Z","verdict_version":"phase8_v1","overall_posture":"watchful","summary":"This cycle centered on AI’s Full Life Cycle Environmental Footprint, with posture watchful and Civitas caution at low.","top_priorities":["AI’s Full Life Cycle Environmental Footprint","DeepTCR: Deep Learning for T‑Cell Repertoire Pattern Discovery","Ensemble Deep Learning for TCR–Peptide Immunogenicity"],"top_risks":["Coverage is brittle because the source base is still narrow.","The read leans heavily on one or two amplification actors.","Coverage is brittle because the source base is still narrow.","The read leans heavily on one or two amplification actors.","Coverage is brittle because the source base is still narrow."],"top_opportunities":["Instrument Tighten posture around the governed weak points more directly before using it as a decision signal.","Instrument Deploy a proof-pack against the main approval blocker more directly before using it as a decision signal.","Instrument Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard more directly before using it as a decision signal.","Instrument Tighten posture around the governed weak points more directly before using it as a decision signal.","Check whether a commercial wedge sits underneath the apparently neutral update."],"recommended_next_actions":["Instrument Tighten posture around the governed weak points more directly before using it as a decision signal.","Instrument Deploy a proof-pack against the main approval blocker more directly before using it as a decision signal.","Instrument Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard more directly before using it as a decision signal.","Instrument Tighten posture around the governed weak points more directly before using it as a decision signal.","Are there commercial interests behind the AI’s Full Life Cycle Environmental Footprint narrative?","Who benefits if AI’s Full Life Cycle Environmental Footprint gains mainstream acceptance?"],"monitor_only_items":["AI’s Full Life Cycle Environmental Footprint: pressure remains low enough for monitor-only tracking.","DeepTCR: Deep Learning for T‑Cell Repertoire Pattern Discovery: pressure remains low enough for monitor-only tracking.","Ensemble Deep Learning for TCR–Peptide Immunogenicity: pressure remains low enough for monitor-only tracking."],"linked_artifact_count":10,"linked_adjudication_count":0,"linked_proposal_count":0,"confidence_summary":{"confidence_score":35.8,"confidence_band":"low","ambiguity_score":0.0,"data_sparsity_score":0.0,"novelty_risk_score":100.0,"causal_weakness_score":0.0,"uncertainty_score":20.0,"uncertainty_band":"low","summary":"Confidence is low at 35.8/100; uncertainty is low at 20.0/100.","reasons":["Confidence is low because evidence sufficiency is 12.9/100 and corroboration is 0.0/100.","Uncertainty is low because ambiguity/data sparsity combine to 20.0/100."],"factors":[{"name":"evidence_sufficiency","value":12.9,"reason":"Confidence should track how much grounded evidence Orbital actually has."},{"name":"corroboration","value":0.0,"reason":"Independent reinforcement raises confidence."},{"name":"ambiguity","value":0.0,"reason":"Ambiguous or conflicting evidence should raise uncertainty."},{"name":"data_sparsity","value":0.0,"reason":"Thin data should keep confidence bounded."},{"name":"novelty_risk","value":100.0,"reason":"New patterns deserve more caution than recurring ones."},{"name":"causal_weakness","value":0.0,"reason":"Derived or correlative reads should carry extra uncertainty."}]},"audience_reasoning":{"reasoning_version":"phase7_v1","summary":"Audience reasoning lands hardest with Procurement and CEO / Founder; Procurement is currently strongest, while Regulator remains the weakest fit. Early audience posture remains visible for Board, CEO / Founder.","most_relevant_audiences":["Procurement","CEO / Founder"],"highest_urgency_audiences":["Procurement","Board"],"early_audiences":["Board","CEO / Founder","Procurement","Regulator","Operator / CISO"],"mature_audiences":[],"developing_audiences":[],"strongest_audience":"Procurement","weakest_audience":"Regulator","audience_deltas":[{"audience_slug":"board","audience_label":"Board","relevance_score":42.5,"relevance_label":"low","relevance_delta":-2.6,"confidence_score":29.11,"confidence_label":"low","confidence_delta":-0.88,"maturity":"early","maturity_score":8.59,"urgency":"low","urgency_score":35.0,"proof_burden":"high","care_score":39.25,"cares_most":false,"declared_signal_count":0,"evidence_signal_count":0,"outcome_signal_count":0,"reasoning_basis":"weak","reasons":[]},{"audience_slug":"ceo_founder","audience_label":"CEO / Founder","relevance_score":46.36,"relevance_label":"medium","relevance_delta":1.26,"confidence_score":31.03,"confidence_label":"low","confidence_delta":1.04,"maturity":"early","maturity_score":8.94,"urgency":"low","urgency_score":34.0,"proof_burden":"medium","care_score":41.01,"cares_most":false,"declared_signal_count":0,"evidence_signal_count":0,"outcome_signal_count":0,"reasoning_basis":"weak","reasons":[]},{"audience_slug":"procurement","audience_label":"Procurement","relevance_score":57.29,"relevance_label":"medium","relevance_delta":12.19,"confidence_score":32.25,"confidence_label":"low","confidence_delta":2.26,"maturity":"early","maturity_score":13.08,"urgency":"low","urgency_score":40.29,"proof_burden":"high","care_score":49.87,"cares_most":true,"declared_signal_count":1,"evidence_signal_count":1,"outcome_signal_count":0,"reasoning_basis":"mixed","reasons":["Aggregated evidence hits: 1 evidence signals and 0 outcome signals."]},{"audience_slug":"regulator","audience_label":"Regulator","relevance_score":36.79,"relevance_label":"low","relevance_delta":-8.31,"confidence_score":27.75,"confidence_label":"low","confidence_delta":-2.24,"maturity":"early","maturity_score":5.16,"urgency":"low","urgency_score":35.0,"proof_burden":"very_high","care_score":36.03,"cares_most":false,"declared_signal_count":0,"evidence_signal_count":0,"outcome_signal_count":0,"reasoning_basis":"weak","reasons":[]},{"audience_slug":"operator_ciso","audience_label":"Operator / CISO","relevance_score":42.57,"relevance_label":"low","relevance_delta":-2.53,"confidence_score":29.82,"confidence_label":"low","confidence_delta":-0.17,"maturity":"early","maturity_score":8.87,"urgency":"low","urgency_score":34.29,"proof_burden":"high","care_score":39.04,"cares_most":false,"declared_signal_count":0,"evidence_signal_count":0,"outcome_signal_count":0,"reasoning_basis":"weak","reasons":[]}],"strongest_interventions_by_audience":[{"audience_slug":"board","audience_label":"Board","strongest_interventions":["Deploy a proof-pack against the main approval blocker","Tighten posture around the governed weak points"],"weakest_interventions":["Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard","Tighten posture around the governed weak points"]},{"audience_slug":"ceo_founder","audience_label":"CEO / Founder","strongest_interventions":["Deploy a proof-pack against the main approval blocker","Tighten posture around the governed weak points"],"weakest_interventions":["Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard","Tighten posture around the governed weak points"]},{"audience_slug":"procurement","audience_label":"Procurement","strongest_interventions":["Deploy a proof-pack against the main approval blocker","Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard"],"weakest_interventions":["Tighten posture around the governed weak points"]},{"audience_slug":"regulator","audience_label":"Regulator","strongest_interventions":["Deploy a proof-pack against the main approval blocker","Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard"],"weakest_interventions":["Tighten posture around the governed weak points"]},{"audience_slug":"operator_ciso","audience_label":"Operator / CISO","strongest_interventions":["Deploy a proof-pack against the main approval blocker","Tighten posture around the governed weak points"],"weakest_interventions":["Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard","Tighten posture around the governed weak points"]}],"learned_intervention_patterns":["Learning posture is neutral: 0 confirming outcome(s), 0 falsifying outcome(s), 0 traction signal(s), and governance history 0/0/0 accepted/rejected/revised.","Learning posture is drag: 0 confirming outcome(s), 0 falsifying outcome(s), 0 traction signal(s), and governance history 0/0/0 accepted/rejected/revised."]},"retrospective":{"retrospective_version":"phase8_v1","summary":"Orbital's prior call broke: the leader moved from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`. Confidence moved up: 31.6 -> 35.8; uncertainty 22.1 -> 20.0. Intervention learning shows 0 strengthening, 0 traction-bearing, 0 falsified, and 4 stalled intervention thread(s). Promotion retrospect is fragile: useful-source confidence 12.0/100, 0 useful promoted source(s), 0 weak source(s), and 0 narrow reinforcement case(s).","what_we_thought":["Prior call: This cycle centered on From Applying Techniques to Advancing Foundations in AI, with posture watchful and Civitas caution at low."],"what_happened":["This cycle: This cycle centered on AI’s Full Life Cycle Environmental Footprint, with posture watchful and Civitas caution at low.","Decisive evidence: AI’s Full Life Cycle Environmental Footprint carried the strongest cross-lane signal with market-shaping confidence 12.9/100 and AI’s Full Life Cycle Environmental Footprint is spreading through 1 source(s) across 1 lane(s) with a clustered amplification posture...","Audience fit landed strongest with Procurement and weakest with Regulator."],"what_changed":["Orbital's prior call broke: the leader moved from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`.","AI’s Full Life Cycle Environmental Footprint","DeepTCR: Deep Learning for T‑Cell Repertoire Pattern Discovery","Ensemble Deep Learning for TCR–Peptide Immunogenicity","The battlefield leader changed from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`.","Confidence moved up: 31.6 -> 35.8; uncertainty 22.1 -> 20.0."],"what_strengthened":[],"what_died":["Intervention weakened or died: Tighten posture around the governed weak points.","Intervention weakened or died: Deploy a proof-pack against the main approval blocker.","Intervention weakened or died: Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard.","Coverage is brittle because the source base is still narrow.","The read leans heavily on one or two amplification actors."],"what_we_learned":["Orbital's prior call broke: the leader moved from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`.","Confidence improved while uncertainty stayed bounded, so the current call has become more believable.","Intervention posture is reinforcing for 0 thread(s) and weakening for 4.","Audience fit is strongest for Procurement and weakest for Regulator.","Early audience posture remains visible for Board, CEO / Founder.","Promotion retrospect is fragile: useful-source confidence 12.0/100, 0 useful promoted source(s), 0 weak source(s), and 0 narrow reinforcement case(s)."],"watch_next":["AI’s Full Life Cycle Environmental Footprint: pressure remains low enough for monitor-only tracking.","DeepTCR: Deep Learning for T‑Cell Repertoire Pattern Discovery: pressure remains low enough for monitor-only tracking.","Ensemble Deep Learning for TCR–Peptide Immunogenicity: pressure remains low enough for monitor-only tracking."],"confidence_shift":{"direction":"up","current_confidence_score":35.8,"prior_confidence_score":31.6,"current_uncertainty_score":20.0,"prior_uncertainty_score":22.1,"confidence_delta":4.2,"uncertainty_delta":-2.1,"summary":"Confidence moved up: 31.6 -> 35.8; uncertainty 22.1 -> 20.0."},"battlefield_shift":{"direction":"leader_changed","current_leader":"AI’s Full Life Cycle Environmental Footprint","prior_leader":"From Applying Techniques to Advancing Foundations in AI","summary":"The battlefield leader changed from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`."},"intervention_posture":{"strengthened_intervention_count":0,"traction_intervention_count":0,"falsified_intervention_count":0,"stalled_intervention_count":4,"strongest_interventions":[],"weakest_interventions":["Tighten posture around the governed weak points","Deploy a proof-pack against the main approval blocker","Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard"],"summary":"Intervention learning shows 0 strengthening, 0 traction-bearing, 0 falsified, and 4 stalled intervention thread(s)."},"retrospective_health_score":86.0},"strongest_evidence_summary":"AI’s Full Life Cycle Environmental Footprint carried the strongest cross-lane signal with market-shaping confidence 12.9/100 and AI’s Full Life Cycle Environmental Footprint is spreading through 1 source(s) across 1 lane(s) with a clustered amplification posture..","strongest_contradiction_summary":"This could still be a mixed signal where one visible lane is louder than the market as a whole.","governed_outcome_summary":"Civitas history for this workspace is low caution with revise rate 0% and hold rate 0%.","linked_artifact_refs":[{"artifact_kind":"ranked_theme","artifact_type":"theme","artifact_id":"95966a21-8fbf-427e-9f93-f75b4ccdfc03","title":"AI’s Full Life Cycle Environmental 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posture around the governed weak points","status":"draft","generated_at":"2026-05-06T06:15:31.189397+00:00","metadata":{"channel":"Operator memo + leadership narrative","audience":"Executive sponsors and governance reviewers"}},{"artifact_kind":"intervention","artifact_type":"pack_deployment","artifact_id":"1fca81b8-ea6f-45d8-a67d-236317bae93d","title":"Deploy a proof-pack against the main approval blocker","status":"draft","generated_at":"2026-05-06T06:15:31.189397+00:00","metadata":{"channel":"Executive brief + proof pack","audience":"Procurement, legal, and risk reviewers"}},{"artifact_kind":"intervention","artifact_type":"narrative_shift","artifact_id":"dab5e02d-0fb5-4adb-bfa4-e093fa6d3778","title":"Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard","status":"draft","generated_at":"2026-05-06T06:15:31.189397+00:00","metadata":{"channel":"Podcast brief + weekly post sequence","audience":"Executive sponsors and procurement stakeholders"}},{"artifact_kind":"intervention","artifact_type":"message_push","artifact_id":"c04b2073-f641-4967-9327-e5b87ca27f4c","title":"Tighten posture around the governed weak points","status":"draft","generated_at":"2026-05-05T06:20:24.054204+00:00","metadata":{"channel":"Operator memo + leadership narrative","audience":"Executive sponsors and governance reviewers"}},{"artifact_kind":"pack","artifact_type":"scenario_pack","artifact_id":"7ed95914-9929-424d-97fe-1532e96c4e61","title":"Scenario Pack — Weekly intervention rehearsal — Deploy a proof-pack against the main approval blocker — 2026-05-05","status":"ready","generated_at":"2026-05-04T08:46:27.444482+00:00","metadata":{"pack_version":"prompt31_v1"}},{"artifact_kind":"pack","artifact_type":"scenario_pack","artifact_id":"6ad0e481-2d74-4d7f-a51d-5fc7e604907f","title":"Scenario Pack — Weekly opportunity alignment scaffold — 2026-05-05","status":"ready","generated_at":"2026-05-04T08:46:27.410917+00:00","metadata":{"pack_version":"prompt31_v1"}},{"artifact_kind":"pack","artifact_type":"scenario_pack","artifact_id":"52ff1bc4-e662-4607-8fc5-6f5b706a7d3c","title":"Scenario Pack — Weekly risk pressure scaffold — 2026-05-05","status":"ready","generated_at":"2026-05-04T08:46:27.358036+00:00","metadata":{"pack_version":"prompt31_v1"}}],"linked_adjudications":[],"linked_proposals":[],"details":{"omega_version":"prompt_s4_v1","retrospective":{"summary":"Orbital's prior call broke: the leader moved from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`. Confidence moved up: 31.6 -> 35.8; uncertainty 22.1 -> 20.0. Intervention learning shows 0 strengthening, 0 traction-bearing, 0 falsified, and 4 stalled intervention thread(s). Promotion retrospect is fragile: useful-source confidence 12.0/100, 0 useful promoted source(s), 0 weak source(s), and 0 narrow reinforcement case(s).","what_died":["Intervention weakened or died: Tighten posture around the governed weak points.","Intervention weakened or died: Deploy a proof-pack against the main approval blocker.","Intervention weakened or died: Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard.","Coverage is brittle because the source base is still narrow.","The read leans heavily on one or two amplification actors."],"watch_next":["AI’s Full Life Cycle Environmental Footprint: pressure remains low enough for monitor-only tracking.","DeepTCR: Deep Learning for T‑Cell Repertoire Pattern Discovery: pressure remains low enough for monitor-only tracking.","Ensemble Deep Learning for TCR–Peptide Immunogenicity: pressure remains low enough for monitor-only tracking."],"what_changed":["Orbital's prior call broke: the leader moved from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`.","AI’s Full Life Cycle Environmental Footprint","DeepTCR: Deep Learning for T‑Cell Repertoire Pattern Discovery","Ensemble Deep Learning for TCR–Peptide Immunogenicity","The battlefield leader changed from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`.","Confidence moved up: 31.6 -> 35.8; uncertainty 22.1 -> 20.0."],"what_happened":["This cycle: This cycle centered on AI’s Full Life Cycle Environmental Footprint, with posture watchful and Civitas caution at low.","Decisive evidence: AI’s Full Life Cycle Environmental Footprint carried the strongest cross-lane signal with market-shaping confidence 12.9/100 and AI’s Full Life Cycle Environmental Footprint is spreading through 1 source(s) across 1 lane(s) with a clustered amplification posture...","Audience fit landed strongest with Procurement and weakest with Regulator."],"what_we_learned":["Orbital's prior call broke: the leader moved from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`.","Confidence improved while uncertainty stayed bounded, so the current call has become more believable.","Intervention posture is reinforcing for 0 thread(s) and weakening for 4.","Audience fit is strongest for Procurement and weakest for Regulator.","Early audience posture remains visible for Board, CEO / Founder.","Promotion retrospect is fragile: useful-source confidence 12.0/100, 0 useful promoted source(s), 0 weak source(s), and 0 narrow reinforcement case(s)."],"what_we_thought":["Prior call: This cycle centered on From Applying Techniques to Advancing Foundations in AI, with posture watchful and Civitas caution at low."],"confidence_shift":{"summary":"Confidence moved up: 31.6 -> 35.8; uncertainty 22.1 -> 20.0.","direction":"up","confidence_delta":4.2,"uncertainty_delta":-2.1,"prior_confidence_score":31.6,"prior_uncertainty_score":22.1,"current_confidence_score":35.8,"current_uncertainty_score":20.0},"battlefield_shift":{"summary":"The battlefield leader changed from `From Applying Techniques to Advancing Foundations in AI` to `AI’s Full Life Cycle Environmental Footprint`.","direction":"leader_changed","prior_leader":"From Applying Techniques to Advancing Foundations in AI","current_leader":"AI’s Full Life Cycle Environmental Footprint"},"what_strengthened":[],"intervention_posture":{"summary":"Intervention learning shows 0 strengthening, 0 traction-bearing, 0 falsified, and 4 stalled intervention thread(s).","weakest_interventions":["Tighten posture around the governed weak points","Deploy a proof-pack against the main approval blocker","Reframe From Applying Techniques to Advancing Foundations in AI into the buyer proof standard"],"strongest_interventions":[],"stalled_intervention_count":4,"traction_intervention_count":0,"falsified_intervention_count":0,"strengthened_intervention_count":0},"retrospective_version":"phase8_v1","retrospective_health_score":86.0},"top_theme_ids":["95966a21-8fbf-427e-9f93-f75b4ccdfc03","97da5654-dc21-455a-843d-de01d122aa98","bd4398aa-4e39-464c-b9c6-65d291b13c12","8463d3e3-f129-4583-8b21-d026f6f7ef3e","17057613-4c6a-46b7-a92a-28773ae5b167"],"top_theme_names":["AI’s Full Life Cycle Environmental Footprint","DeepTCR: Deep Learning for T‑Cell Repertoire Pattern Discovery","Ensemble Deep Learning for TCR–Peptide Immunogenicity","Automation as a Tool for Wage Suppression, Not Productivity","BERT and the Computational Linguistics Backbone of Modern AI"],"promotion_policy":{"governance":{"posture":"challenge_needed","summary":"Promotion governance is challenge_needed: mode balanced, threshold 0.40, concentration risk 0.0/100, usefulness confidence 12.0/100, and Civitas caution low.","warnings":["Promoted-source history is not broadening the source base enough across distinct themes and corroborating lanes.","Confidence in promoted-source usefulness is still thin, so new admission should stay tightly bounded until more assessable outcomes arrive."],"guardrails":["Beachhead-risk and contradiction-first mission shaping stay active.","Per-mind first-pass cap is bounded at 3 source(s) and is inspectable.","Adaptive thresholding is constrained to [0.38, 0.42] — current threshold is 0.400.","Usefulness-confidence gating is inspectable at 12.0/100 and only applies bounded threshold moves."],"recommendations":["Civitas has no adjudication history for this workspace yet. Governance posture is based entirely on promoted-source quality outcomes. Civitas threshold pressure will engage once the first bundle is adjudicated."],"civitas_informed":false,"challenge_findings":[],"governance_version":"adaptive_governance_v3","civitas_caution_level":"low","civitas_adjudication_count":0,"civitas_challenge_pressure_score":0.0},"adaptive_mode":"balanced","retrospection":{"summary":"Promotion retrospect is fragile: useful-source confidence 12.0/100, 0 useful promoted source(s), 0 weak source(s), and 0 narrow reinforcement case(s).","what_died":[],"what_we_learned":["Admission confidence is 12.0/100 because assessable history is 0 source(s).","Pending queue still leans toward `pricing_value`.","Quality posture is weak while concentration posture is controlled."],"what_strengthened":[],"retrospective_version":"phase8_v1"},"adaptive_hooks":{"posture":"fragile","summary":"Adaptive admission is fragile: usefulness confidence 12.0/100, promotion readiness 28.0/100, and mode balanced.","hook_version":"phase8_v1","bounded_actions":["Beachhead-risk and contradiction-first mission shaping stay active.","Per-mind first-pass cap is bounded at 3 source(s) and is inspectable.","Adaptive thresholding is constrained to [0.38, 0.42] — current threshold is 0.400.","Usefulness-confidence gating is inspectable at 12.0/100 and only applies bounded threshold moves."],"loosening_pressures":["Diversity health is still only 0.0/100.","Weak-source rate is controlled at 0%."],"tightening_pressures":["Usefulness-confidence score is only 12.0/100."],"promotion_readiness_score":28.0,"usefulness_confidence_score":12.0},"quality_posture":"weak","promotion_readiness_score":28.0,"usefulness_confidence_score":12.0},"audience_reasoning":{"summary":"Audience reasoning lands hardest with Procurement and CEO / Founder; Procurement is currently strongest, while Regulator remains the weakest fit. Early audience posture remains visible for Board, CEO / Founder.","audience_deltas":[{"reasons":[],"urgency":"low","maturity":"early","care_score":39.25,"cares_most":false,"proof_burden":"high","audience_slug":"board","urgency_score":35.0,"audience_label":"Board","maturity_score":8.59,"reasoning_basis":"weak","relevance_delta":-2.6,"relevance_label":"low","relevance_score":42.5,"confidence_delta":-0.88,"confidence_label":"low","confidence_score":29.11,"outcome_signal_count":0,"declared_signal_count":0,"evidence_signal_count":0,"maturity_has_early_signal":true,"maturity_has_mature_signal":false},{"reasons":[],"urgency":"low","maturity":"early","care_score":41.01,"cares_most":false,"proof_burden":"medium","audience_slug":"ceo_founder","urgency_score":34.0,"audience_label":"CEO / Founder","maturity_score":8.94,"reasoning_basis":"weak","relevance_delta":1.26,"relevance_label":"medium","relevance_score":46.36,"confidence_delta":1.04,"confidence_label":"low","confidence_score":31.03,"outcome_signal_count":0,"declared_signal_count":0,"evidence_signal_count":0,"maturity_has_early_signal":true,"maturity_has_mature_signal":false},{"reasons":["Aggregated evidence hits: 1 evidence signals and 0 outcome signals."],"urgency":"low","maturity":"early","care_score":49.87,"cares_most":true,"proof_burden":"high","audience_slug":"procurement","urgency_score":40.29,"audience_label":"Procurement","maturity_score":13.08,"reasoning_basis":"mixed","relevance_delta":12.19,"relevance_label":"medium","relevance_score":57.29,"confidence_delta":2.26,"confidence_label":"low","confidence_score":32.25,"outcome_signal_count":0,"declared_signal_count":1,"evidence_signal_count":1,"maturity_has_early_signal":true,"maturity_has_mature_signal":false},{"reasons":[],"urgency":"low","maturity":"early","care_score":36.03,"cares_most":false,"proof_burden":"very_high","audience_slug":"regulator","urgency_score":35.0,"audience_label":"Regulator","maturity_score":5.16,"reasoning_basis":"weak","relevance_delta":-8.31,"relevance_label":"low","relevance_score":36.79,"confidence_delta":-2.24,"confidence_label":"low","confidence_score":27.75,"outcome_signal_count":0,"declared_signal_count":0,"evidence_signal_count":0,"maturity_has_early_signal":true,"maturity_has_mature_signal":false},{"reasons":[],"urgency":"low","maturity":"early","care_score":39.04,"cares_most":false,"proof_burden":"high","audience_slug":"operator_ciso","urgency_score":34.29,"audience_label":"Operator 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