{"id":"W4385950679","doi":"10.1007/978-3-031-05735-9_25-1","title":"Pipeline Emergency Response Protocols and Incident Investigation","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Pipeline (software); Pipeline transport; Incident response; Risk analysis (engineering); Focus (optics); Containment (computer programming); Computer science; Service (business); Emergency response; Engineering; Computer security; Forensic engineering; Business; Medical emergency; Medicine; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006306132,0.0008050553,0.000299479,0.001183128,0.001178006,0.003403786,0.0008691931,0.001907077,0.04552822],"category_scores_gemma":[0.001747578,0.0004195197,0.0002317284,0.001719778,0.001228605,0.003722915,0.001258028,0.00206377,0.01964468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002304125,"about_ca_system_score_gemma":0.002558915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007067338,"about_ca_topic_score_gemma":0.01285658,"domain_scores_codex":[0.9994856,0.0001477227,0.00002210575,0.00004644662,0.0002557314,0.00004230417],"domain_scores_gemma":[0.9994997,0.0002771298,0.00002642275,0.00004364841,0.0001291524,0.00002395546],"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":[0.000009411397,0.00003798179,0.00006534206,0.000169242,0.000002212408,0.00008532735,0.0005071163,0.001746344,0.0003103401,0.3564133,0.443294,0.1973595],"study_design_scores_gemma":[0.00000101069,0.000006784227,0.00009353447,0.0001879429,0.000001366979,0.00006883992,0.0002406315,0.0004844615,0.000116514,0.03813574,0.9606578,0.000005436172],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003524364,0.006069806,0.01302677,0.002485431,0.001415015,0.00007285949,0.0001266011,0.0001414805,0.9763095],"genre_scores_gemma":[0.004860192,0.008916324,0.004348935,0.000978509,0.000366646,0.00007514214,0.0001778171,0.000121984,0.9801543],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04552822,"threshold_uncertainty_score":0.1523071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02993534240191646,"score_gpt":0.2400630545818007,"score_spread":0.2101277121798843,"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."}}