{"id":"W2589523396","doi":"10.71781/939","title":"Patient and physician characteristics as predictors for consent to participate in an electronic medical record study","year":2004,"lang":"en","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Patient Dignity and Privacy","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Université de Montréal; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; McGill University; U.S. Department of Health and Human Services","keywords":"Electronic medical record; Medical record; Family medicine; Medicine; Medical education; Psychology; Data science; Computer science; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005618185,0.0001195133,0.000254608,0.0007822586,0.0009676514,0.001360182,0.0004430807,0.00122213,0.00452214],"category_scores_gemma":[0.09063752,0.000211366,0.0004333284,0.001656762,0.0006240496,0.001157234,0.0005622663,0.001729477,0.0003865427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003791474,"about_ca_system_score_gemma":0.002244393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002684669,"about_ca_topic_score_gemma":0.004552895,"domain_scores_codex":[0.9939323,0.003531501,0.0008245874,0.0002485014,0.0008915929,0.000571529],"domain_scores_gemma":[0.8856109,0.07870204,0.0219928,0.003779139,0.00276122,0.007153922],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005215125,0.0003415427,0.9948716,0.00002441259,0.00004232968,0.000176302,0.0006266879,0.00004472449,0.0001202922,0.0001295633,0.0004709077,0.002630106],"study_design_scores_gemma":[0.00007116691,0.0004277791,0.994412,0.00005566836,0.00006067828,0.0005653668,0.00251476,0.0005651749,0.0002239591,0.0003297309,0.0007578557,0.00001595515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965424,0.0002050697,0.0001068426,0.0009378085,0.00002534625,0.00006678451,0.0004014042,0.000003284685,0.001711097],"genre_scores_gemma":[0.9989045,0.0001234393,0.0002059317,0.0001890168,0.00002644461,0.00002805473,0.0001729153,0.000003743768,0.000346102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9943818,"threshold_uncertainty_score":0.02971214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463448229844622,"score_gpt":0.2463360776044045,"score_spread":0.2317015953059583,"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."}}