Use for cross-country RISK RANKING, not precise within-country day-of-shutdown timing.
This forecast scores the ONSET of a new recorded incident, not how censored a country already is. A permanently and stably blocked network generates no new anomaly, so it scores LOW. Measured 2026-07-31: China 0.015 and India 0.023 both rank BELOW Denmark 0.062 — China is probed 30/30 days across 836 domains and has logged nothing for 71 days, while Denmark is probed 2/30 days. A low score here means 'no CHANGE expected', never 'this country is free'. For standing severity use /v1/atlas/score-v2 or the censorship index instead.
Training ROC AUC 0.954 came from a RANDOM stratified split (consecutive country-days in an incident window are near-duplicates, inflating it). No target leakage: features use [date-7,date], label uses [date+1,date+7].
ML_LEAKAGE_AUDIT.md (forecast v1/7day row).
Complete returned record
{
"aci": {
"active": false,
"reason": "unverified: training holdout and ACI outcomes do not match the served headline or qualified target"
},
"aci_alpha": null,
"confidence": 0.85,
"country": "ZW",
"country_name": "Zimbabwe",
"covered": true,
"forecast": [
{
"date": "2026-10-12",
"day": 0,
"drivers": [],
"risk": 0.01
},
{
"date": "2026-10-13",
"day": 1,
"drivers": [],
"risk": 0.022
},
{
"date": "2026-10-14",
"day": 2,
"drivers": [],
"risk": 0.01
},
{
"date": "2026-10-15",
"day": 3,
"drivers": [],
"risk": 0.018
},
{
"date": "2026-10-16",
"day": 4,
"drivers": [],
"risk": 0.01
},
{
"date": "2026-10-17",
"day": 5,
"drivers": [],
"risk": 0.039
},
{
"date": "2026-10-18",
"day": 6,
"drivers": [],
"risk": 0.045
},
{
"date": "2026-10-19",
"day": 7,
"drivers": [],
"risk": 0.036
}
],
"forecast_trajectory_note": "summary.max_risk comes from honest_forecast_v1, an EXPERIMENTAL score: its historical rolling-origin AUC (~0.815) did not hold in live use (recent monthly live AUC 0.26-0.29, worse than chance). No proven onset-timing skill; do not cite it as a forecast. Re-evaluation: B1602 (2026-10). The per-day forecast[] trajectory is the legacy v1 illustrative shape; the v1 value is kept as max_risk_v1_leaky.",
"generated_at": "2026-10-12T13:03:26.177240",
"honest_caveat": {
"confidence_is": "fixed in-sample model confidence, NOT a per-forecast calibrated probability",
"correct_use": "Use for cross-country RISK RANKING, not precise within-country day-of-shutdown timing.",
"detects_change_not_state": "This forecast scores the ONSET of a new recorded incident, not how censored a country already is. A permanently and stably blocked network generates no new anomaly, so it scores LOW. Measured 2026-07-31: China 0.015 and India 0.023 both rank BELOW Denmark 0.062 — China is probed 30/30 days across 836 domains and has logged nothing for 71 days, while Denmark is probed 2/30 days. A low score here means 'no CHANGE expected', never 'this country is free'. For standing severity use /v1/atlas/score-v2 or the censorship index instead.",
"headline_auc_note": "Training ROC AUC 0.954 came from a RANDOM stratified split (consecutive country-days in an incident window are near-duplicates, inflating it). No target leakage: features use [date-7,date], label uses [date+1,date+7].",
"honest_temporal_holdout_auc": "~0.85-0.90 (dual-holdout temporal gate)",
"live_forward_accountability": [
"GET /v1/sentinel/accuracy (503 unvalidated; empirical precision/recall withheld)",
"GET /v1/forecast/onset-skill (honest onset / forward skill)"
],
"source": "ML_LEAKAGE_AUDIT.md (forecast v1/7day row)."
},
"honest_forecast": {
"as_of": "2026-10-11",
"flag": false,
"is_headline_source": true,
"probability": 0.0824,
"recommended_threshold": 0.675,
"risk_band": "low",
"semantics": "probability of a censorship/connectivity EVENT in the next 7 days (country-relative z-score label)",
"validation": "Historical backtest only: rolling-origin AUC ~0.815, PR-AUC ~0.29. It did NOT hold in live use (recent monthly live AUC 0.26-0.29, worse than chance). Experimental; under re-evaluation (B1602). Do not cite as a validated forecast."
},
"interval_90": null,
"model_version": "honest_forecast_v1",
"summary": {
"avg_risk": 0.024,
"key_drivers": [],
"max_risk": 0.0824,
"max_risk_day": 6,
"max_risk_v1_leaky": 0.045
},
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": -0.0272,
"direction": "down",
"name": "block_rate_roll7_mean",
"source": "model"
}
],
"top_features_per_day": [
{
"base_prob": 0,
"date": "2026-10-12",
"day": 0,
"risk": 0.01,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": -0.0272,
"direction": "down",
"name": "block_rate_roll7_mean",
"source": "model"
}
]
},
{
"base_prob": 0,
"date": "2026-10-13",
"day": 1,
"risk": 0.022,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": -0.0272,
"direction": "down",
"name": "block_rate_roll7_mean",
"source": "model"
}
]
},
{
"base_prob": 0,
"date": "2026-10-14",
"day": 2,
"risk": 0.01,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": -0.0272,
"direction": "down",
"name": "block_rate_roll7_mean",
"source": "model"
}
]
},
{
"base_prob": 0,
"date": "2026-10-15",
"day": 3,
"risk": 0.018,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": -0.0272,
"direction": "down",
"name": "block_rate_roll7_mean",
"source": "model"
}
]
},
{
"base_prob": 0,
"date": "2026-10-16",
"day": 4,
"risk": 0.01,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": -0.0272,
"direction": "down",
"name": "block_rate_roll7_mean",
"source": "model"
}
]
},
{
"base_prob": 0,
"date": "2026-10-17",
"day": 5,
"risk": 0.039,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": -0.0272,
"direction": "down",
"name": "block_rate_roll7_mean",
"source": "model"
}
]
},
{
"base_prob": 0,
"date": "2026-10-18",
"day": 6,
"risk": 0.045,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": 0.03,
"direction": "up",
"name": "day_decay_t+6",
"source": "overlay"
}
]
},
{
"base_prob": 0,
"date": "2026-10-19",
"day": 7,
"risk": 0.036,
"top_features": [
{
"contribution": -0.0855,
"direction": "down",
"name": "block_rate_roll30_mean",
"source": "model"
},
{
"contribution": -0.0444,
"direction": "down",
"name": "gdelt_unrest_30d",
"source": "model"
},
{
"contribution": 0.035,
"direction": "up",
"name": "day_decay_t+7",
"source": "overlay"
}
]
}
]
}