{"id":"W2933369404","doi":"10.1016/j.scib.2019.04.003","title":"Increasing the value of weather-related warnings","year":2019,"lang":"en","type":"article","venue":"Science Bulletin","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":70,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Value (mathematics); Environmental science; Meteorology; Geography; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00394193,0.00006077433,0.00008501632,0.00007465594,0.0005611541,0.000107305,0.00100725,0.00002889553,0.001373603],"category_scores_gemma":[0.0004187959,0.00003941436,0.00004119218,0.000829114,0.002006881,0.0001325896,0.0001623203,0.00008587482,0.0007417184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003379026,"about_ca_system_score_gemma":0.0001379799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001582086,"about_ca_topic_score_gemma":0.00001641841,"domain_scores_codex":[0.9984024,0.0001606364,0.0001489985,0.0002235951,0.0007394802,0.0003249474],"domain_scores_gemma":[0.9993807,0.0001465366,0.0001122838,0.0002294725,0.0000729907,0.00005799083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004011046,0.0001369012,0.1006535,0.00003331546,0.00001986559,0.000003690284,0.1473807,0.0003517098,0.02645471,0.6954997,0.005891478,0.02353437],"study_design_scores_gemma":[0.0004014094,0.00009899717,0.06512399,0.0001509345,0.0000209758,0.000002608843,0.05234163,0.0006712642,0.000846619,0.005169673,0.8748516,0.0003203257],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.693027,0.00003413355,0.000007193728,0.005082169,0.0002694843,0.00016878,1.717821e-7,0.00002437763,0.3013867],"genre_scores_gemma":[0.9775041,0.00001448311,0.0001567919,0.0001865951,0.00002476696,0.000002096239,1.174566e-7,0.000003415883,0.02210761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8689601,"threshold_uncertainty_score":0.9995393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005183392815402238,"score_gpt":0.2529060848800698,"score_spread":0.2477226920646676,"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."}}