{"id":"W2022201065","doi":"10.1002/met.198","title":"Public perception of and response to severe weather warnings in Nova Scotia, Canada","year":2010,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Nova scotia; Vulnerability (computing); Warning system; Nova (rocket); Social vulnerability; Geography; Perception; Social media; Political science; Psychology; Computer science; Aeronautics; Engineering; Computer security; Psychological intervention; Telecommunications","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":[0.0004303521,0.0001503949,0.0001521669,0.0005292053,0.002155903,0.001015205,0.0003428848,0.0002792282,0.00224979],"category_scores_gemma":[0.002450445,0.0001428075,0.000142615,0.0006213517,0.0009011114,0.0001945846,0.0008568346,0.000461611,0.0001420566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01017766,"about_ca_system_score_gemma":0.01005117,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9810191,"about_ca_topic_score_gemma":0.9880216,"domain_scores_codex":[0.9995215,0.0000678108,0.00002349466,0.00003719646,0.0001427484,0.000207258],"domain_scores_gemma":[0.9976357,0.0003072523,0.0006106691,0.00004757263,0.0007062347,0.0006925848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003009865,0.0000926259,0.9256676,0.0001182791,0.00003818648,0.001510045,0.04953068,0.0003025477,0.002050727,0.0002838256,0.003620464,0.01648413],"study_design_scores_gemma":[0.000006597361,0.000059672,0.9344503,0.00005643972,0.00000725067,0.00008989296,0.0623599,0.0001585906,0.000133267,0.0000230932,0.002638457,0.0000165058],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962664,0.00008545964,0.00001512792,0.0004309902,0.000008461585,0.00001699671,0.0001669849,0.000001688986,0.003007967],"genre_scores_gemma":[0.998654,0.0001392034,0.00002257004,0.00008574012,0.000002387462,0.000005470984,0.00006286164,8.564836e-7,0.001026845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01898092,"threshold_uncertainty_score":0.07384443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555171229604938,"score_gpt":0.2835700620128075,"score_spread":0.2580183497167582,"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."}}