{"id":"W4312393449","doi":"10.1115/ipc2022-86832","title":"CSA EXP16: Human and Organizational Factors for Optimal Pipeline Performance","year":2022,"lang":"en","type":"article","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Standards Association; Alberta Energy","funders":"","keywords":"Pipeline (software); Scope (computer science); Knowledge management; Subject-matter expert; Harm; Computer science; Best practice; Process management; Engineering; Management","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":[0.02572741,0.001092895,0.0004374647,0.002261383,0.003268153,0.007858792,0.001711534,0.003115749,0.03200013],"category_scores_gemma":[0.04010019,0.0004586807,0.0009400813,0.001852536,0.003590135,0.003766845,0.004748538,0.004607199,0.008482652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004971988,"about_ca_system_score_gemma":0.03000317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01073754,"about_ca_topic_score_gemma":0.01364699,"domain_scores_codex":[0.9856982,0.005051952,0.001032447,0.0006783134,0.006910784,0.0006283491],"domain_scores_gemma":[0.9246184,0.02662214,0.005179921,0.00475602,0.03556889,0.003254604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003029534,0.001056397,0.0189579,0.002945961,0.0000543037,0.0006045697,0.006133174,0.006496978,0.006129367,0.1627311,0.4644139,0.3301735],"study_design_scores_gemma":[0.00009739611,0.0007056653,0.04738697,0.004602766,0.00004852349,0.0003839516,0.006375763,0.003804614,0.008515484,0.04548519,0.8823822,0.0002115138],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1032011,0.00771916,0.06521167,0.1493461,0.004716358,0.006556963,0.007092358,0.001390985,0.6547654],"genre_scores_gemma":[0.556091,0.01161756,0.1736614,0.01867354,0.00275398,0.005855897,0.008602694,0.0008521224,0.2218919],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03200013,"threshold_uncertainty_score":0.1360611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07973873487390722,"score_gpt":0.3529209726746233,"score_spread":0.2731822378007161,"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."}}