{"id":"W4398474265","doi":"10.7910/dvn/itvlik/psu38r","title":"Disaster_events_dates_keeperL.tab","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Natural disaster; Natural (archaeology); Geography; Environmental resource management; Environmental science; Meteorology; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001130578,0.00212052,0.001507068,0.004675361,0.0007889948,0.003371864,0.002825922,0.00268327,0.1948368],"category_scores_gemma":[0.007278383,0.001077237,0.001281329,0.008640644,0.0005697159,0.002247061,0.002342435,0.001701785,0.1447612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002248092,"about_ca_system_score_gemma":0.002473638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02857198,"about_ca_topic_score_gemma":0.03455575,"domain_scores_codex":[0.9991455,0.0001289008,0.00013199,0.000247414,0.0001838048,0.0001624191],"domain_scores_gemma":[0.9972077,0.0008615018,0.0003250212,0.000673385,0.0005916364,0.0003407463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003379413,0.000009515352,0.0004616791,0.0006103998,0.00002314336,0.00001145125,0.00001935911,0.0002246858,0.00005310052,0.0008157201,0.9963797,0.001357477],"study_design_scores_gemma":[0.0001974948,0.00001086609,0.002231652,0.0003874521,0.00002675971,0.00003240866,0.00006140192,0.0003468536,0.0003087472,0.001750977,0.9946122,0.00003322354],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003426229,0.00003006333,0.00003572987,0.00005784908,0.00001638762,0.000004986729,0.9989948,0.0002732273,0.0005528248],"genre_scores_gemma":[0.0005600611,0.00009877376,0.0002199983,0.000101476,0.00001216143,0.0000637504,0.9979638,0.0001890853,0.0007908735],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8051631,"threshold_uncertainty_score":0.6517942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063915542382391,"score_gpt":0.2827773796812504,"score_spread":0.2621382242574265,"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."}}