{"id":"W2131630297","doi":"10.1016/s0010-4825(02)00015-x","title":"The TEAM methodology for the evaluation of information systems in biomedicine","year":2002,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke","funders":"","keywords":"Computer science; Dimension (graph theory); Relation (database); Information system; Biomedicine; Stakeholder; Perspective (graphical); Information flow; Management science; Risk analysis (engineering); Process management; Operations research; Data mining; Artificial intelligence; Engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002005035,0.00005292514,0.0001270925,0.0001173577,0.00002511953,0.000001696086,0.00007900975,0.00007363372,0.000002653908],"category_scores_gemma":[0.0002783732,0.00002658902,0.000007296284,0.000167471,0.0001805837,0.00002661251,0.000008502187,0.00008361565,4.40283e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002831067,"about_ca_system_score_gemma":0.000004523238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004499053,"about_ca_topic_score_gemma":0.000008861087,"domain_scores_codex":[0.9994814,0.00006753471,0.00024548,0.00004670319,0.00005680074,0.000102113],"domain_scores_gemma":[0.998779,0.001058904,0.00002907321,0.00008147925,0.00003379642,0.00001774524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001719918,0.00001577659,0.001000596,0.0003352774,0.00004838871,8.869642e-8,0.003697458,0.007331617,0.0009294488,0.01023092,0.01278903,0.9636042],"study_design_scores_gemma":[0.00104651,0.0001074386,0.01319947,0.0001127234,0.00001937421,0.000006606243,0.0004517019,0.9565158,0.00001736268,0.001354984,0.0271258,0.00004221295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1886819,0.1253527,0.6390373,0.020036,0.02258489,0.002570385,0.000009776551,0.0001349136,0.001592202],"genre_scores_gemma":[0.9973112,0.001726121,0.0006267659,0.00007652692,0.0001673988,0.00007239374,0.00001340601,0.000002552655,0.000003668674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.963562,"threshold_uncertainty_score":0.1084269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07976968600212687,"score_gpt":0.344170228582787,"score_spread":0.2644005425806601,"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."}}