{"id":"b730ebba-094a-42f9-bc5a-7fe0ec35443f","workspace_slug":"orbital","window_days":7,"window_start":"2026-05-05T00:00:00Z","window_end":"2026-05-12T00:00:00Z","generated_at":"2026-05-11T06:13:31.967430Z","verdict_version":"phase8_v1","overall_posture":"watchful","summary":"This cycle centered on DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires, with posture watchful and Civitas caution at low.","top_priorities":["DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires","Ensemble Deep Learning for TCR–Peptide Immunogenicity Prediction","Agentic AI as a Force Multiplier for Cyber Offense"],"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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires narrative?","Who benefits if DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires gains mainstream acceptance?"],"monitor_only_items":["DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires: pressure remains low enough for monitor-only tracking.","Ensemble Deep Learning for TCR–Peptide Immunogenicity Prediction: pressure remains low enough for monitor-only tracking.","Agentic AI as a Force Multiplier for Cyber Offense: pressure remains low enough for monitor-only tracking."],"linked_artifact_count":10,"linked_adjudication_count":1,"linked_proposal_count":0,"confidence_summary":{"confidence_score":34.8,"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 34.8/100; uncertainty is low at 20.0/100.","reasons":["Confidence is low because evidence sufficiency is 10.6/100 and corroboration is 0.0/100.","Uncertainty is low because ambiguity/data sparsity combine to 20.0/100."],"factors":[{"name":"evidence_sufficiency","value":10.6,"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":-1.06,"confidence_score":29.11,"confidence_label":"low","confidence_delta":-0.34,"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":2.8,"confidence_score":31.03,"confidence_label":"low","confidence_delta":1.58,"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":50.71,"relevance_label":"medium","relevance_delta":7.15,"confidence_score":30.11,"confidence_label":"low","confidence_delta":0.66,"maturity":"early","maturity_score":8.87,"urgency":"low","urgency_score":40.29,"proof_burden":"high","care_score":46.26,"cares_most":true,"declared_signal_count":1,"evidence_signal_count":0,"outcome_signal_count":0,"reasoning_basis":"declared_audience_only","reasons":["This audience remains mostly declared-targeting language without stronger evidence carry-through."]},{"audience_slug":"regulator","audience_label":"Regulator","relevance_score":36.79,"relevance_label":"low","relevance_delta":-6.77,"confidence_score":27.75,"confidence_label":"low","confidence_delta":-1.7,"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":41.43,"relevance_label":"low","relevance_delta":-2.13,"confidence_score":29.25,"confidence_label":"low","confidence_delta":-0.2,"maturity":"early","maturity_score":8.59,"urgency":"low","urgency_score":34.0,"proof_burden":"high","care_score":38.24,"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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences into the buyer proof standard","Tighten posture around the governed weak points"]}],"learned_intervention_patterns":["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 `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`. Confidence moved flat: 34.7 -> 34.8; uncertainty 20.0 -> 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 0.0/100, 0 useful promoted source(s), 1 weak source(s), and 1 narrow reinforcement case(s).","what_we_thought":["Prior call: This cycle centered on DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences, with posture watchful and Civitas caution at low."],"what_happened":["This cycle: This cycle centered on DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires, with posture watchful and Civitas caution at low.","Decisive evidence: DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires carried the strongest cross-lane signal with market-shaping confidence 10.6/100 and DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires 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 `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`.","DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires","Ensemble Deep Learning for TCR–Peptide Immunogenicity Prediction","Agentic AI as a Force Multiplier for Cyber Offense","The battlefield leader changed from `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`."],"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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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.","1 promoted source(s) produced little downstream value."],"what_we_learned":["Orbital's prior call broke: the leader moved from `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`.","Confidence did not materially de-risk the call, so operator posture should stay bounded.","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 0.0/100, 0 useful promoted source(s), 1 weak source(s), and 1 narrow reinforcement case(s)."],"watch_next":["DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires: pressure remains low enough for monitor-only tracking.","Ensemble Deep Learning for TCR–Peptide Immunogenicity Prediction: pressure remains low enough for monitor-only tracking.","Agentic AI as a Force Multiplier for Cyber Offense: pressure remains low enough for monitor-only tracking."],"confidence_shift":{"direction":"flat","current_confidence_score":34.8,"prior_confidence_score":34.7,"current_uncertainty_score":20.0,"prior_uncertainty_score":20.0,"confidence_delta":0.1,"uncertainty_delta":0.0,"summary":"Confidence moved flat: 34.7 -> 34.8; uncertainty 20.0 -> 20.0."},"battlefield_shift":{"direction":"leader_changed","current_leader":"DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires","prior_leader":"DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences","summary":"The battlefield leader changed from `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`."},"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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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":82.0},"strongest_evidence_summary":"DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires carried the strongest cross-lane signal with market-shaping confidence 10.6/100 and DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires 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":"49eca0aa-cf9d-40ef-b7f8-8a15dd292a59","title":"DeepTCR: 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2026-05-05","status":"ready","generated_at":"2026-05-04T08:46:27.358036+00:00","metadata":{"pack_version":"prompt31_v1"}}],"linked_adjudications":[{"id":"06e13d4c-43da-4b38-a35a-dc012e1f84c1","handoff_bundle_id":"5c45e4b6-0eb5-49c3-9e9f-49476a5116f0","status":"heartbeat_succeeded","final_verdict":null,"publishable_as_is":false,"scope_status":null,"fallback_status":null,"fallback_reason":null,"manual_review_required":false,"coverage_fraction":null,"scope_within_capability":false,"submitted_at":"2026-05-11T06:13:31.200601Z","completed_at":"2026-05-11T06:13:31.421692Z","created_at":"2026-05-11T06:13:31.201873Z"}],"linked_proposals":[],"details":{"omega_version":"prompt_s4_v1","retrospective":{"summary":"Orbital's prior call broke: the leader moved from `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`. Confidence moved flat: 34.7 -> 34.8; uncertainty 20.0 -> 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 0.0/100, 0 useful promoted source(s), 1 weak source(s), and 1 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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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.","1 promoted source(s) produced little downstream value."],"watch_next":["DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires: pressure remains low enough for monitor-only tracking.","Ensemble Deep Learning for TCR–Peptide Immunogenicity Prediction: pressure remains low enough for monitor-only tracking.","Agentic AI as a Force Multiplier for Cyber Offense: pressure remains low enough for monitor-only tracking."],"what_changed":["Orbital's prior call broke: the leader moved from `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`.","DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires","Ensemble Deep Learning for TCR–Peptide Immunogenicity Prediction","Agentic AI as a Force Multiplier for Cyber Offense","The battlefield leader changed from `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`."],"what_happened":["This cycle: This cycle centered on DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires, with posture watchful and Civitas caution at low.","Decisive evidence: DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires carried the strongest cross-lane signal with market-shaping confidence 10.6/100 and DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires 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 `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`.","Confidence did not materially de-risk the call, so operator posture should stay bounded.","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 0.0/100, 0 useful promoted source(s), 1 weak source(s), and 1 narrow reinforcement case(s)."],"what_we_thought":["Prior call: This cycle centered on DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences, with posture watchful and Civitas caution at low."],"confidence_shift":{"summary":"Confidence moved flat: 34.7 -> 34.8; uncertainty 20.0 -> 20.0.","direction":"flat","confidence_delta":0.1,"uncertainty_delta":0.0,"prior_confidence_score":34.7,"prior_uncertainty_score":20.0,"current_confidence_score":34.8,"current_uncertainty_score":20.0},"battlefield_shift":{"summary":"The battlefield leader changed from `DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences` to `DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires`.","direction":"leader_changed","prior_leader":"DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences","current_leader":"DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires"},"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 DeepTCR: Deep Learning to Decode T‑Cell Receptor Sequences 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":82.0},"top_theme_ids":["49eca0aa-cf9d-40ef-b7f8-8a15dd292a59","40094bba-8d8c-4786-ac38-7f31cc8f79c9","1449a460-3f78-4d4b-9136-3a43eff2de10","e3a9b9e0-0089-4749-80b7-486aaca7754d","148b1644-94bf-4ac6-8e18-2c4fb7b1ad75"],"top_theme_names":["DeepTCR: Deep Learning to Decode T‑Cell Receptor Repertoires","Ensemble Deep Learning for TCR–Peptide Immunogenicity Prediction","Agentic AI as a Force Multiplier for Cyber Offense","Christopher Koch’s Emerging Role in Agentic AI Cyber Offense Discourse","AI’s Full Life Cycle Environmental Footprint"],"promotion_policy":{"governance":{"posture":"challenge_needed","summary":"Promotion governance is challenge_needed: mode balanced, threshold 0.40, concentration risk 100.0/100, usefulness confidence 0.0/100, and Civitas caution low.","warnings":["Promoted-source history is concentrating around `narrative_warfare` and should keep challenger promotion pressure high.","Promoted-source history is not broadening the source base enough across distinct themes and corroborating lanes.","1 Search Council auto-promoted source(s) are recommended for quarantine because they only reinforce the dominant cluster without downstream value.","1 domain family/families are in cooldown because they keep resurfacing without useful lift.","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 0.0/100 and only applies bounded threshold moves."],"recommendations":["Quarantine weak Search Council auto-promoted sources before the next promotion batch so they stop shaping live ranking, theme generation, and ingestion selection.","Keep cooled domain families out of the next promotion batch unless they arrive with corroboration or multi-mind support.","Pending queue is dominated by `narrative_warfare` (100% share). Prefer challenger-mind candidates in the next promotion batch to reduce concentration."],"civitas_informed":true,"challenge_findings":[],"governance_version":"adaptive_governance_v3","civitas_caution_level":"low","civitas_adjudication_count":10,"civitas_challenge_pressure_score":0.0},"adaptive_mode":"balanced","retrospection":{"summary":"Promotion retrospect is fragile: useful-source confidence 0.0/100, 0 useful promoted source(s), 1 weak source(s), and 1 narrow reinforcement case(s).","what_died":["1 promoted source(s) produced little downstream value.","1 promoted source(s) only reinforced narrow clusters.","1 promoted source(s) are quarantine candidates."],"what_we_learned":["Admission confidence is 0.0/100 because assessable history is 1 source(s).","Pending queue still leans toward `pricing_value`.","Quality posture is weak while concentration posture is high_risk."],"what_strengthened":[],"retrospective_version":"phase8_v1"},"adaptive_hooks":{"posture":"fragile","summary":"Adaptive admission is fragile: usefulness confidence 0.0/100, promotion readiness 0.0/100, 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 0.0/100 and only applies bounded threshold moves."],"loosening_pressures":["Diversity health is still only 0.0/100."],"tightening_pressures":["Weak-source rate is elevated at 100%.","Concentration risk remains 100.0/100.","Usefulness-confidence score is only 0.0/100."],"promotion_readiness_score":0.0,"usefulness_confidence_score":0.0},"quality_posture":"weak","promotion_readiness_score":0.0,"usefulness_confidence_score":0.0},"audience_reasoning":{"summary":"Audience reasoning lands hardest with Procurement and CEO / Founder; Procurement is currently strongest, while Regulator remains the weakest fit. 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