{"id":"W3135613023","doi":"10.1007/s41781-021-00069-9","title":"Software Training in HEP","year":2021,"lang":"en","type":"preprint","venue":"Computing and Software for Big Science","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Division of Advanced Cyberinfrastructure; Office of Advanced Cyberinfrastructure; National Science Foundation","keywords":"Computer science; Software development; Software; Software engineering; Domain (mathematical analysis); Engineering management; Knowledge management; Engineering; 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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002777498,0.0004594351,0.0007375946,0.000465859,0.0007362498,0.002078588,0.00287259,0.0002716509,5.182297e-7],"category_scores_gemma":[0.001871687,0.0004780822,0.0001604314,0.001592588,0.0003665448,0.0002746415,0.003781885,0.0006849344,0.000001968874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001561905,"about_ca_system_score_gemma":0.002305024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001150812,"about_ca_topic_score_gemma":0.00003265304,"domain_scores_codex":[0.995441,0.000117132,0.0007034531,0.002006795,0.0006598727,0.001071775],"domain_scores_gemma":[0.9969565,0.0007428823,0.0003713924,0.001081044,0.0005533978,0.0002947912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007661015,0.0001050551,0.01094125,0.001043773,0.00003398334,0.0001060331,0.02501993,0.1003027,0.00007057116,0.002453498,0.000339521,0.859576],"study_design_scores_gemma":[0.001334665,0.0002197393,0.01698917,0.005135452,0.00002535491,0.0002603032,0.0009790332,0.9555414,0.0001535467,0.01337257,0.003658743,0.002330037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1823034,0.001199391,0.8101954,0.0001389063,0.005162338,0.0003883466,0.00002003185,0.0005359506,0.00005626062],"genre_scores_gemma":[0.7772849,0.00001274657,0.2221023,0.000144989,0.0003444671,0.00001894531,0.00003504354,0.00001895022,0.00003758886],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.857246,"threshold_uncertainty_score":0.9997671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05055294693954814,"score_gpt":0.2945330931740947,"score_spread":0.2439801462345465,"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."}}