{"id":"W6939464133","doi":"10.6084/m9.figshare.21541971","title":"Additional file 1 of Validating administrative data to identify complex surgical site infections following cardiac implantable electronic device implantation: a comparison of traditional methods and machine learning","year":2022,"lang":"en","type":"article","venue":"Open MIND","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Alberta; University of Calgary","funders":"","keywords":"Patient data; Key (lock); Data collection; MEDLINE","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002283338,0.0007490762,0.0006666867,0.002134572,0.000848364,0.0009688271,0.001146458,0.0009361312,0.6094083],"category_scores_gemma":[0.05330531,0.0003371758,0.0007262888,0.003260183,0.0002319689,0.001171258,0.0007777906,0.0007820063,0.04043624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187302,"about_ca_system_score_gemma":0.002490968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01240373,"about_ca_topic_score_gemma":0.01734976,"domain_scores_codex":[0.9981193,0.0003528227,0.0005259651,0.0002916093,0.0005512239,0.0001590918],"domain_scores_gemma":[0.9443631,0.03585885,0.007609373,0.002857783,0.008631599,0.0006793041],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005235165,0.000238166,0.01492224,0.001531188,0.00008485466,0.00007427728,0.00008965182,0.0005175809,0.0001089713,0.0008566421,0.9706098,0.01044303],"study_design_scores_gemma":[0.01007161,0.00120156,0.2904888,0.007627229,0.000496335,0.001192078,0.001754957,0.004886566,0.00224276,0.008958166,0.6708059,0.0002741845],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.001023324,0.00001076348,0.0002123093,0.0001008896,0.00001526487,0.0001519697,0.997438,0.00007161099,0.0009758651],"genre_scores_gemma":[0.02956404,0.0001006846,0.003442365,0.000551943,0.0001300447,0.003729154,0.9542812,0.0002629457,0.007937659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9977167,"threshold_uncertainty_score":0.5571317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6082138837792227,"score_gpt":0.5930145957868498,"score_spread":0.01519928799237291,"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."}}