{"id":"W3143266486","doi":"10.1016/j.mex.2021.101333","title":"A dynamic version of the FRAM for capturing variability in complex operations","year":2021,"lang":"en","type":"article","venue":"MethodsX","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon Health Network; Saint John Regional Hospital; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation de la recherche en santé du Nouveau-Brunswick","keywords":"Computer science; Data science; Function (biology); Systems engineering; Complex system; Engineering; Artificial intelligence; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.004040887,0.00005124227,0.0001650012,0.00003825036,0.0004726776,0.000002147873,0.0001220486,0.00009815615,0.0003739882],"category_scores_gemma":[0.004837883,0.00003791422,0.00005718446,0.00030039,0.00004614131,0.00003640198,0.0001207395,0.0003551921,0.00000991925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001838221,"about_ca_system_score_gemma":0.0008897207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004913167,"about_ca_topic_score_gemma":0.001163438,"domain_scores_codex":[0.9960995,0.002943699,0.0003737937,0.0001625988,0.000167134,0.0002532386],"domain_scores_gemma":[0.9949878,0.004299643,0.00004526506,0.0002987884,0.0003126265,0.00005581143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001180517,0.0009502933,0.7672083,0.00642577,0.00005874627,0.000004109137,0.01470192,0.006979212,0.03334844,0.06248859,0.002236336,0.1044178],"study_design_scores_gemma":[0.0007921439,0.00002186382,0.9168342,0.00008524083,0.000005644009,3.376691e-7,0.0006077132,0.0668299,0.0002571995,0.006760883,0.007752242,0.00005259595],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6782805,0.0001540062,0.2900808,0.01705326,0.001196893,0.004050061,0.000458116,0.00003257769,0.008693776],"genre_scores_gemma":[0.7720392,0.00001283025,0.2263894,0.000458279,0.00003790833,0.0002443288,0.000062948,0.000008418948,0.0007466811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.149626,"threshold_uncertainty_score":0.5791747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1932234697103528,"score_gpt":0.5737103691464583,"score_spread":0.3804868994361055,"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."}}