{"id":"W2582654140","doi":"10.1115/ipc2016-64166","title":"CSA EXP248: Pipeline Human Factors","year":2016,"lang":"en","type":"article","venue":"","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Standards Association","funders":"","keywords":"Pipeline (software); Computer science; Process (computing); Risk analysis (engineering); Task (project management); Asset (computer security); Service (business); Engineering; Knowledge management; Process management; Systems engineering; Computer security; Business; Marketing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01478361,0.001796016,0.0006854711,0.003671356,0.004440181,0.006611339,0.003538063,0.007567347,0.09905446],"category_scores_gemma":[0.02437381,0.0009740814,0.001699924,0.002457913,0.00243035,0.004714398,0.005074952,0.006651454,0.07991742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004258669,"about_ca_system_score_gemma":0.02414453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02118951,"about_ca_topic_score_gemma":0.02350341,"domain_scores_codex":[0.9843816,0.002689784,0.001266801,0.0007509688,0.00985339,0.001057514],"domain_scores_gemma":[0.9538237,0.004803899,0.001944145,0.003288078,0.03314112,0.002998964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00008431976,0.0001648763,0.0004301407,0.0009087215,0.00001009321,0.0002164238,0.0005010159,0.0006072379,0.003492577,0.02112667,0.8631608,0.1092973],"study_design_scores_gemma":[0.00001103186,0.0000648757,0.0008401631,0.0004818804,0.000003821537,0.0001596739,0.0001157358,0.0001225656,0.0008440791,0.001292948,0.9960401,0.00002308203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006487825,0.009873087,0.04841322,0.04908468,0.01443117,0.004060357,0.008211448,0.00856629,0.850872],"genre_scores_gemma":[0.04858153,0.01593501,0.05730229,0.02557661,0.003983072,0.004430347,0.01711137,0.00345697,0.8236228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09905446,"threshold_uncertainty_score":0.3313702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2031895459118214,"score_gpt":0.5450001301122405,"score_spread":0.341810584200419,"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."}}