{"id":"W3215510267","doi":"10.1002/acm2.13477","title":"Topic modeling of maintenance logs for linac failure modes and trends identification","year":2021,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Quality and Safety in Healthcare","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"","keywords":"Computer science; Identification (biology); Ranking (information retrieval); Downtime; Linear particle accelerator; Failure mode and effects analysis; Data science; Reliability engineering; Artificial intelligence; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.003429578,0.0001044331,0.0006698028,0.00003159948,0.0001793038,0.000004745352,0.0001939903,0.0004283511,0.00005637424],"category_scores_gemma":[0.002085305,0.00008307157,0.0002138374,0.0001677901,0.0001496092,0.0000730722,0.00007674233,0.001300724,0.000003152937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004029322,"about_ca_system_score_gemma":0.0005917863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006067454,"about_ca_topic_score_gemma":0.00002014044,"domain_scores_codex":[0.9963663,0.000294906,0.00234871,0.0002013235,0.0005284297,0.0002603572],"domain_scores_gemma":[0.9949162,0.002832742,0.0009428446,0.0002241821,0.000768043,0.0003160011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001489191,0.0009143641,0.002514649,0.003017497,0.0002581459,0.00001865147,0.002748644,0.0009408515,0.0003256871,0.3998924,0.006340163,0.5815398],"study_design_scores_gemma":[0.008802542,0.0007330139,0.004130984,0.002821576,0.0003237706,0.00001432525,0.01556119,0.1341765,0.0003304702,0.8236315,0.009051523,0.0004226413],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4720427,0.0006631513,0.4553419,0.06692624,0.001770276,0.0005564876,0.00007081268,0.00003168202,0.002596776],"genre_scores_gemma":[0.991429,0.0007797881,0.003979062,0.001867894,0.001786913,0.00001483938,0.00001312651,0.00001336968,0.0001159833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5811172,"threshold_uncertainty_score":0.565107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2050213516941972,"score_gpt":0.5277297247776579,"score_spread":0.3227083730834607,"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."}}