{"id":"W4239537783","doi":"10.1503/cmaj.181018","title":"Code blue","year":2018,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Earthquake and Disaster Impact Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Courtesy; Computer science; Computer graphics (images); Computer security; Art; Philosophy; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0009784447,0.001257928,0.0007043103,0.001657515,0.001544109,0.004079994,0.002112179,0.001927693,0.8931403],"category_scores_gemma":[0.009508019,0.0007358441,0.0008493189,0.001188807,0.0006452595,0.003857417,0.00407029,0.002051232,0.849272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001094222,"about_ca_system_score_gemma":0.001824353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01474308,"about_ca_topic_score_gemma":0.01758111,"domain_scores_codex":[0.9993711,0.00007800847,0.00003079625,0.0001061781,0.0002982623,0.0001155597],"domain_scores_gemma":[0.9958715,0.0006124412,0.0001239605,0.000619805,0.002087899,0.0006844128],"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":[0.00001418267,0.000005101784,0.00005266189,0.00004604002,8.086309e-7,0.000009734737,0.00002367127,0.00002200815,0.00004687653,0.0005828649,0.9857032,0.01349289],"study_design_scores_gemma":[0.00001417277,0.000005155595,0.0002505181,0.00007116068,0.000001953757,0.00003179008,0.00004049315,0.00006996583,0.0001348714,0.001042914,0.9983224,0.0000145951],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"editorial","genre_scores_codex":[0.0004827572,0.0002895097,0.009533389,0.004668422,0.003988749,0.0004105164,0.0643494,0.1091372,0.8071401],"genre_scores_gemma":[0.004052032,0.0004054061,0.008793543,0.006556615,0.0005796329,0.0006676378,0.04304804,0.05243246,0.8834645],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.8931403,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01791234306187415,"score_gpt":0.3016230516214246,"score_spread":0.2837107085595504,"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."}}