{"id":"W3210022287","doi":"10.2196/31551","title":"Peer Review of “Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method”","year":2021,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health records; Peer review; Psychology; Health care; Medicine; Medical emergency; Political science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07019279,0.0009732224,0.001938095,0.00690548,0.005737353,0.008416466,0.003031796,0.0042944,0.06341314],"category_scores_gemma":[0.4380637,0.0007273843,0.001641436,0.004324056,0.005339942,0.006088125,0.005246133,0.005151025,0.04834877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003510386,"about_ca_system_score_gemma":0.01933087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004349589,"about_ca_topic_score_gemma":0.008063627,"domain_scores_codex":[0.8995466,0.04366305,0.009739299,0.003567656,0.04141341,0.002069884],"domain_scores_gemma":[0.3164155,0.05141988,0.01059781,0.02141766,0.5913567,0.00879236],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003527189,0.00001386238,0.0002613807,0.0008484308,0.00003076137,0.0001103071,0.000592048,0.00003737055,0.0003173983,0.0009092265,0.9610911,0.03575283],"study_design_scores_gemma":[0.00003710572,0.00003417166,0.001086343,0.001622917,0.00003101524,0.0001766094,0.0007838449,0.000471613,0.0006132078,0.001813263,0.9932851,0.00004474904],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.002849412,0.003619679,0.02270265,0.4147724,0.5058817,0.003395195,0.001764027,0.002029921,0.0429849],"genre_scores_gemma":[0.08448377,0.0180623,0.05864981,0.1544768,0.3336153,0.005163661,0.006543232,0.005815458,0.3331897],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9298072,"threshold_uncertainty_score":0.3712194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05457645250794923,"score_gpt":0.4608801531424119,"score_spread":0.4063037006344626,"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."}}