{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002318947,0.000101152,0.000425834,0.0001139241,0.001477149,0.00002147898,0.0002592108,0.00005654426,0.4492254],"category_scores_gemma":[0.0008587434,0.0001054492,0.00004292357,0.0003317635,0.00002815528,0.0002965805,0.0005198114,0.0007450239,0.0000533579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000110152,"about_ca_system_score_gemma":0.0008533994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002817783,"about_ca_topic_score_gemma":0.0001876471,"domain_scores_codex":[0.9969126,0.001348093,0.0008382084,0.000241356,0.0003616413,0.0002980853],"domain_scores_gemma":[0.9903404,0.008721396,0.000540447,0.0001686443,0.00008575193,0.0001433965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003355724,0.0003047388,0.008296448,0.0003478864,0.0002484552,0.000004391381,0.0113721,0.0003050001,0.0009751776,0.0003667444,0.934844,0.04259947],"study_design_scores_gemma":[0.0005258629,0.0003997506,0.007247823,0.0002047963,0.00005142136,0.00002287452,0.004978652,0.006391327,0.00005992129,0.000038119,0.979959,0.0001204486],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1416252,0.00006186304,0.001201739,0.000294173,0.0002222569,0.001352995,0.8362232,0.00000995213,0.01900862],"genre_scores_gemma":[0.3814625,0.000006131867,0.06552361,0.0001234207,0.0001366579,0.0007192736,0.5514469,0.00001555077,0.0005659325],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4491721,"threshold_uncertainty_score":0.9998228,"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."}}