{"id":"W6962799346","doi":"10.17605/osf.io/ps97e","title":"The performance of machine learning algorithm in surgical site infections case identification and prediction, a scoping review protocol (Addendum for DOI: 10.17605/OSF.IO/F8ERZ)","year":2022,"lang":"en","type":"other","venue":"Open Science Framework","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Surgical site infection; Protocol (science); Health care; Quality (philosophy); Medical record; Infection control; Patient care","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0391981,0.001660143,0.005913207,0.01247291,0.002586785,0.004534188,0.002591766,0.003869523,0.08045609],"category_scores_gemma":[0.07561528,0.001523368,0.007093281,0.008633254,0.001531128,0.003819957,0.003655018,0.002145667,0.007536255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006025169,"about_ca_system_score_gemma":0.04511603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005971453,"about_ca_topic_score_gemma":0.01540106,"domain_scores_codex":[0.9831875,0.004804031,0.007941259,0.001113769,0.002480041,0.0004733344],"domain_scores_gemma":[0.9751902,0.01057451,0.003928961,0.001451132,0.008325861,0.0005293635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.001040593,0.0001519576,0.0006607407,0.8747407,0.001111951,0.0001721561,0.0004828367,0.0003664748,0.0005024159,0.002182238,0.03250414,0.08608397],"study_design_scores_gemma":[0.002471452,0.0007550112,0.00414815,0.8026702,0.008478124,0.0002612214,0.0006630872,0.0004543677,0.0009694739,0.002751352,0.1762611,0.000116347],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.00349197,0.09888253,0.008291185,0.006140777,0.00199625,0.7984551,0.06919064,0.0004666819,0.01308488],"genre_scores_gemma":[0.006472399,0.06332831,0.01987215,0.002082568,0.0002516935,0.8957431,0.008769157,0.00007451863,0.003406143],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.08045609,"threshold_uncertainty_score":0.2691524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437321226033803,"score_gpt":0.377543433814941,"score_spread":0.353170221554603,"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."}}