{"id":"W3187105191","doi":"10.3389/feart.2021.684084","title":"An Earthquake Early Warning System for Southwestern British Columbia","year":2021,"lang":"en","type":"article","venue":"Frontiers in Earth Science","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Ocean Networks Canada Society; University of Victoria","funders":"Natural Resources Canada; Canada Foundation for Innovation; Government of Canada; BC Hydro; Australian Government; Public Safety Canada","keywords":"Geodetic datum; Seismology; Earthquake warning system; Geology; GNSS applications; Warning system; Submarine pipeline; Epicenter; Seismic hazard; Global Positioning System; Early warning system; Geodesy; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002989404,0.0003476073,0.0001909823,0.001259048,0.001541183,0.001160746,0.0005729104,0.000319484,0.009774585],"category_scores_gemma":[0.001393299,0.0001656643,0.00008263345,0.0014214,0.0001230799,0.0004487821,0.000605511,0.0004079692,0.002286487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006103732,"about_ca_system_score_gemma":0.0110727,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9325634,"about_ca_topic_score_gemma":0.9567288,"domain_scores_codex":[0.9997862,0.00001529296,0.00001612977,0.00003113516,0.0001038305,0.00004744024],"domain_scores_gemma":[0.9983745,0.00004777396,0.00004554708,0.000059775,0.001319841,0.0001525391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005563317,0.0001951774,0.1016256,0.0002460027,0.00005294395,0.000877942,0.001012884,0.01037179,0.02104423,0.002134201,0.4719152,0.3899676],"study_design_scores_gemma":[0.0003077727,0.0001482964,0.2491488,0.0002947776,0.0001103448,0.0002852173,0.002677178,0.2164569,0.01445183,0.001047797,0.5147883,0.0002827579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6188611,0.001713114,0.03468772,0.009232648,0.000576023,0.001929348,0.09301275,0.03398087,0.2060064],"genre_scores_gemma":[0.8185923,0.001118051,0.03802923,0.0007812998,0.00005941877,0.0004309822,0.05167588,0.0003720926,0.08894081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06743664,"threshold_uncertainty_score":0.1356675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008579994634501318,"score_gpt":0.2146720324434818,"score_spread":0.2060920378089805,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}