{"id":"W2228494091","doi":"","title":"Facilitating medical decision making with collaborative tools","year":2005,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Medical decision making; Data science; Knowledge management; Medicine","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":[0.006637977,0.001129988,0.0006095861,0.002366445,0.001281995,0.006292611,0.002349593,0.002803232,0.01539386],"category_scores_gemma":[0.03537487,0.0005763634,0.0009809812,0.001724527,0.001089953,0.006394746,0.006858401,0.001438196,0.002591368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004239345,"about_ca_system_score_gemma":0.001277047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009122147,"about_ca_topic_score_gemma":0.001179998,"domain_scores_codex":[0.993946,0.003679284,0.0004126381,0.0006021964,0.001060479,0.0002993552],"domain_scores_gemma":[0.9566206,0.03652761,0.0009501206,0.003701766,0.00135087,0.0008489551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009999232,0.001451461,0.005252674,0.0009763791,0.0002987786,0.002494357,0.009431073,0.02548352,0.01979096,0.06704078,0.0150605,0.8517196],"study_design_scores_gemma":[0.001009774,0.001259621,0.004791173,0.00124338,0.0006594296,0.003192058,0.006817141,0.285984,0.05569085,0.4659597,0.1729517,0.0004410656],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06469929,0.000547146,0.8943464,0.001766431,0.0002026834,0.000400199,0.0001929514,0.003073386,0.03477151],"genre_scores_gemma":[0.4907888,0.0005324055,0.501594,0.0003731026,0.000153985,0.0004024354,0.0003292601,0.0001988995,0.00562713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01539386,"threshold_uncertainty_score":0.05149758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02947793901093193,"score_gpt":0.3022616693247762,"score_spread":0.2727837303138442,"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."}}