{"id":"W4311650614","doi":"10.1101/2022.12.02.22283021","title":"CyclOps: Cyclical development towards operationalizing ML models for health","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Hospital for Sick Children; SickKids Foundation; Vector Institute","funders":"","keywords":"Python (programming language); Computer science; Cyclops; Software; Software engineering; Software deployment; Artificial intelligence; Operating system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002416006,0.0003792522,0.0005589908,0.0002237728,0.0007577621,0.0002475276,0.0024263,0.000182437,0.00008162798],"category_scores_gemma":[0.0002294468,0.0003921685,0.0001666462,0.0002423733,0.00002638116,0.0001795727,0.00367848,0.001264989,0.00001301883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007746711,"about_ca_system_score_gemma":0.00354421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002810558,"about_ca_topic_score_gemma":0.00005814442,"domain_scores_codex":[0.9956864,0.0004949211,0.0008936596,0.001330042,0.0009385398,0.0006564956],"domain_scores_gemma":[0.9977606,0.0002025376,0.0003666968,0.001182341,0.0001850195,0.0003028388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003484519,0.0002882727,0.01498461,0.00304347,0.000170403,0.00003346041,0.02147353,0.5367976,0.00001365613,0.2271838,0.005015924,0.1909604],"study_design_scores_gemma":[0.0002831474,0.00009645787,0.01263205,0.0001621319,0.000004267461,0.00001382984,0.00002758314,0.8068174,0.00003048951,0.01441919,0.1649097,0.0006037724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01769513,0.0007868666,0.9378771,0.03843215,0.002084783,0.001409824,0.00003563775,0.0005480957,0.00113042],"genre_scores_gemma":[0.2493099,0.00009794148,0.7405374,0.006214974,0.0004078632,0.002235936,0.0003183124,0.00008065723,0.0007970064],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2700197,"threshold_uncertainty_score":0.999853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0836819863969416,"score_gpt":0.3765165697688245,"score_spread":0.2928345833718828,"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."}}