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Precision @ 0.7
Classic AI models cry wolf at every minor tremor, inflating their accuracy numbers. Talivio works differently. Our system is deliberately under-confident — it never triggers an alert when the evidence is uncertain.
Say goodbye to false alarms. Know only the moments that truly require action.
| Feature / Metric | Traditional Institutions (USGS) | Classical Academic AI | Talivio (Regional ML) |
|---|---|---|---|
| Core Logic | Pure Statistics (only knows aftershocks) | Black-box Classification (memorises) | Physics-Informed AI (Spatial/Temporal) |
| Spatial Resolution | 10–50 km (very broad) | Province or region level | H3 Res 8/9 (0.7 km² pinpoint) |
| Time Horizon | Usually 24 hours | Single & uncertain | 7, 30 & 90-day dynamic probabilities |
| False Positive | Medium | Very high (up to 80% false alarms) | Near-zero ([email protected] = 91%) |
| Probability Calibration (ECE) | None | Usually not measured | 0.032 (excellent calibration) |
| Brier Skill Score (BSS) | 1.5–3% (reference) | Negative (worse than random) | 23.9% (far above industry standard) |
Talivio's performance compared to published earthquake forecasting systems worldwide. Our AUC values use hard same-region negatives — the most rigorous evaluation protocol.
| System | Metric | Value | ASS† | Window | Negatives | Validation |
|---|---|---|---|---|---|---|
| ETAS Italy (OEF-Italy) | Area Skill Score | 0.7 | 0.700 | 1-day | same_region | Prospective |
| RELM California (CSEP) | Probability Gain vs Random | 10 | — | 5-year | same_region | Prospective |
| CSEP California (2011–2020) | IGPE vs Benchmark | 0 | — | 5-year | same_region | Prospective |
| FCN Deep Learning (California) | Area Skill Score | 0.882 | 0.882 | 15–90 day | same_region | Retrospective |
| DeVries 2018 (Google Brain) | AUC | 0.849 | — | static | global_mixed | Retrospective |
| ETAS Japan (CSEP daily) | CSEP Pass Rate | 0.9 | — | 1-day | same_region | Prospective |
| EEPAS New Zealand | IGPE | 0.64 | — | 3-month | same_region | Prospective |
| Talivio v2 | AUC + ASS (Molchan) | 0.619–0.994 | 0.099 | 30-day | Hard same-region | Retrospective + Prospective |
† ASS = Area Skill Score (Molchan, [0,1]). FCN=0.882, ETAS Italy=0.70 (published).
8 regions, 127 backtest years. Full methodology →
Our system has been tested with Walk-forward Validation and a 30-day purge gap protocol to prevent data memorisation.
Each region trains its own ML model. Negative samples are drawn from the same tectonic zone — producing honest AUC values (0.62–0.99 range) with no geographic bias.
Amber band = trained model exists · AUC = expanding-window backtest result (hard same-region negatives)
Seismic Intelligence
Deep dives into earthquake science, AI forecasting models, and seismic risk analysis.
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The Cascadia Subduction Zone poses one of the most significant seismic hazards globally, capable of generating devastating megathrust earthquakes. Talivio leverages advanced AI and machine learning to continuously monitor this critical region, analyzing complex geophysical data to enhance our understanding of its unique tectonic characteristics and potential for future seismic events.
Location Reports
One complete seismic risk analysis for your exact location — 5 magnitude bands, 5 time horizons, fault map, and historical catalog.
Get Your Report — €5This system provides statistical probability forecasts. Earthquake time, location and magnitude cannot be precisely predicted scientifically. Probabilities are based on historical patterns and physical models; they do not imply certainty.