{"id":"W4235428593","doi":"10.1503/cmaj.050598","title":"Patient n plus 1","year":2005,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Healthcare Systems and Practices","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Text mining; Data science; World Wide Web; Medicine; Natural language processing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0005507221,0.0003620388,0.001555692,0.0005036727,0.001175922,0.0005144591,0.0003642883,0.0009069869,0.06724235],"category_scores_gemma":[0.002266426,0.0001862442,0.0005979597,0.0005800676,0.0001878508,0.0005113975,0.0005609553,0.0005614412,0.007566044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003709511,"about_ca_system_score_gemma":0.0007508515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002057765,"about_ca_topic_score_gemma":0.003265223,"domain_scores_codex":[0.9994321,0.0001080747,0.0000771718,0.0001533697,0.0000891591,0.0001400938],"domain_scores_gemma":[0.9996864,0.00008568891,0.00007609891,0.000051985,0.0000389105,0.00006086635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.08877554,0.003577287,0.1979028,0.007220523,0.001457612,0.01004361,0.001075638,0.001155729,0.008312956,0.01040078,0.2845351,0.3855425],"study_design_scores_gemma":[0.01968931,0.01739421,0.2434026,0.002832788,0.001442384,0.01776805,0.001467645,0.001436684,0.002612557,0.01017815,0.6815717,0.0002040333],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"commentary","genre_scores_codex":[0.5877512,0.01962414,0.006037469,0.004224528,0.004552486,0.007739795,0.05744896,0.0004475363,0.3121739],"genre_scores_gemma":[0.8087955,0.004914461,0.002680636,0.0169498,0.001249408,0.007106561,0.01880652,0.00008939103,0.1394076],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.06724235,"threshold_uncertainty_score":0.2249481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04730464740002358,"score_gpt":0.4190613582991296,"score_spread":0.371756710899106,"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."}}