{"id":"W2625362830","doi":"10.1007/s11069-017-2959-3","title":"Logistic models as a forecasting tool for snow avalanches in a cold maritime climate: northern Gaspésie, Québec, Canada","year":2017,"lang":"en","type":"article","venue":"Natural Hazards","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Center for Northern Studies; Université du Québec à Rimouski","funders":"","keywords":"Snow; Natural hazard; Environmental science; Climatology; Meteorology; Logistic regression; Hazard; Physical geography; Geography; Geology; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001568146,0.0004974396,0.000313921,0.001077533,0.0007153613,0.00123659,0.001044217,0.0004149484,0.002932302],"category_scores_gemma":[0.0065937,0.0002616766,0.0003556413,0.001430588,0.0003303958,0.0005158933,0.0004200522,0.000628121,0.0004037952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007234328,"about_ca_system_score_gemma":0.006102546,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9508152,"about_ca_topic_score_gemma":0.9500516,"domain_scores_codex":[0.9997359,0.000111995,0.00001816193,0.00005057854,0.00003446964,0.00004901469],"domain_scores_gemma":[0.9971232,0.001699626,0.0002019171,0.0000832138,0.0007126235,0.0001793577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004132912,0.0001080333,0.1769314,0.00005010512,0.00009712566,0.0001604237,0.0001329195,0.7698852,0.0002454226,0.001743736,0.009917173,0.04031503],"study_design_scores_gemma":[0.00001973082,0.00001586258,0.01471318,0.00001139765,0.00001439754,0.000008768158,0.0001305629,0.9837453,0.00006526331,0.0005666963,0.0006962658,0.00001253981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9475928,0.0009499963,0.03363727,0.002821098,0.00009275513,0.0001279891,0.00924289,0.0005948209,0.004940481],"genre_scores_gemma":[0.9865936,0.0004036131,0.006149293,0.00005752795,0.00002617398,0.00003802815,0.002977495,0.0000369536,0.003717321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0491848,"threshold_uncertainty_score":0.09894884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03855863725485852,"score_gpt":0.2421573897981759,"score_spread":0.2035987525433174,"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."}}