{"id":"W3043783332","doi":"10.1002/aws2.1181","title":"A hydrocarbon pipeline spill risk assessment framework for drinking water supply","year":2020,"lang":"en","type":"article","venue":"AWWA Water Science","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Risk assessment; Oil spill; Water supply; Pipeline (software); Water source; Environmental engineering; Pipeline transport; Upstream (networking); Risk analysis (engineering); Petroleum engineering; Water resource management; Engineering; Computer science; Business","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006969149,0.0001477994,0.0001307367,0.00004000026,0.0004998374,0.0001597519,0.0004358501,0.00005728521,0.0007237283],"category_scores_gemma":[0.00006611433,0.00009233521,0.00006763697,0.0002692194,0.000332547,0.0004625278,0.0003220378,0.0001786767,0.0006207325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001237591,"about_ca_system_score_gemma":0.00001270347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001355963,"about_ca_topic_score_gemma":0.00002746917,"domain_scores_codex":[0.998068,0.00003141678,0.000228947,0.0006010057,0.0005170958,0.0005534814],"domain_scores_gemma":[0.9994356,0.00002447783,0.00004584594,0.0002384032,0.00002105774,0.0002346321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003109001,0.00005288792,0.05929457,0.00001441086,0.000006856304,0.000005365795,0.006194747,0.002111751,0.9028103,0.0004603041,0.0003680787,0.02864958],"study_design_scores_gemma":[0.0003655781,0.0002399423,0.0114873,0.00001392983,0.00002151957,0.000004143065,0.0001337158,0.05390911,0.9042442,0.01275872,0.01651146,0.0003104216],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8752905,0.000003979765,0.1167451,0.004600589,0.0004113182,0.000353668,0.000003809236,0.0001158413,0.002475213],"genre_scores_gemma":[0.9737284,0.000007800611,0.02389507,0.00205717,0.0001246606,0.00004505782,0.000006400088,0.00001376466,0.0001217107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09843788,"threshold_uncertainty_score":0.7978469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108989176193778,"score_gpt":0.2471751035387242,"score_spread":0.2360852117767864,"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."}}