{"id":"W2054143405","doi":"10.5380/ce.v19i3.37972","title":"CARACTERIZAÇÃO DE IDOSOS VÍTIMAS DE ACIDENTES POR CAUSAS EXTERNAS","year":2014,"lang":"pt","type":"article","venue":"Cogitare Enfermagem","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Medicine; Humanities; Art","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":[],"consensus_categories":[],"category_scores_codex":[0.00114665,0.0003239235,0.0005699253,0.001545975,0.0005443979,0.001093303,0.0003062022,0.0004243141,0.001257977],"category_scores_gemma":[0.002722997,0.0005065697,0.0005418363,0.001660949,0.0003713254,0.0003596931,0.0006652675,0.00035991,0.0002365994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007643929,"about_ca_system_score_gemma":0.0009030316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01986345,"about_ca_topic_score_gemma":0.03382507,"domain_scores_codex":[0.9991487,0.0002124136,0.0001290669,0.0001314158,0.000252757,0.0001255901],"domain_scores_gemma":[0.9979252,0.0003034071,0.000941338,0.0001000644,0.000551892,0.0001780852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002210197,0.00003762877,0.9930677,0.0002093649,0.00004689255,0.0001356433,0.0005712126,0.00001581547,0.001188987,0.00002027145,0.00009449412,0.004390959],"study_design_scores_gemma":[0.000008031446,0.000369024,0.9941667,0.0001454275,0.0001087769,0.0007915585,0.001888509,0.00006996116,0.0009488303,0.00003872778,0.001455252,0.000009110669],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922627,0.004061622,0.0002048668,0.00007947227,0.00001551142,0.00009050417,0.001381746,0.000007319475,0.001896206],"genre_scores_gemma":[0.9945273,0.003052892,0.0007564646,0.00009213902,0.00001746561,0.00007114896,0.0005999545,0.000004052695,0.0008786348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01986345,"threshold_uncertainty_score":0.03949565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04046782963697975,"score_gpt":0.3513972073574547,"score_spread":0.3109293777204749,"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."}}