{"id":"W4402188606","doi":"10.3138/cjms.v6i5.15","title":"Ontarian Sonographers’ Awareness of Vasa Previa","year":2015,"lang":"en","type":"article","venue":"˜The œCanadian journal of medical sonography.","topic":"Artificial Intelligence Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Computer science; Medical physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008201954,0.0001104041,0.0001582532,0.000686437,0.0008914533,0.0008211187,0.0003132987,0.0003151562,0.006119065],"category_scores_gemma":[0.00392462,0.0001934773,0.0001435369,0.0008697092,0.0005395742,0.0004236169,0.0004494491,0.0003047309,0.0003341811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001812458,"about_ca_system_score_gemma":0.002939109,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2331927,"about_ca_topic_score_gemma":0.3254551,"domain_scores_codex":[0.999227,0.0001565771,0.00006485774,0.00007576472,0.0002777989,0.0001980755],"domain_scores_gemma":[0.9955009,0.001216622,0.001683585,0.000121013,0.0007453812,0.0007324414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004132488,0.00004508379,0.9762015,0.00009069187,0.000009979583,0.000383195,0.01157214,0.00001523,0.0004918111,0.00004696447,0.0007415377,0.01036051],"study_design_scores_gemma":[0.000004119561,0.00009380603,0.97635,0.00006449352,0.000009702435,0.0003358735,0.02113841,0.00004339994,0.00008684737,0.00001854843,0.001848748,0.00000599164],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959607,0.0002868967,0.0000701229,0.0003985365,0.00001098382,0.00001355013,0.0001402621,0.00000475884,0.003114183],"genre_scores_gemma":[0.9981648,0.0004499992,0.0001182867,0.0002033097,0.000009648003,0.00001119826,0.00007716603,0.00000175923,0.0009638568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7668073,"threshold_uncertainty_score":0.4636707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0711430748278523,"score_gpt":0.3099659757834393,"score_spread":0.238822900955587,"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."}}