{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005135114,0.001356843,0.0006345372,0.002915435,0.001007543,0.002905108,0.002181849,0.001242455,0.003735546],"category_scores_gemma":[0.003793017,0.0005169119,0.001364405,0.001329508,0.001305435,0.001505672,0.001752817,0.001174608,0.000549597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005001625,"about_ca_system_score_gemma":0.009072039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06492324,"about_ca_topic_score_gemma":0.0437725,"domain_scores_codex":[0.9974734,0.001050001,0.0001334315,0.0002196515,0.0009329719,0.0001905136],"domain_scores_gemma":[0.9982724,0.0006324088,0.0001589321,0.00006456181,0.0007771727,0.00009445108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001762774,0.00006005913,0.0008729745,0.0001179182,0.0000592886,0.0002570617,0.0002279178,0.6602589,0.0008062906,0.3152219,0.004733521,0.01736648],"study_design_scores_gemma":[0.00001848166,0.00004658498,0.0003187987,0.0001130017,0.00003996125,0.0000874527,0.0001853324,0.8692041,0.00030953,0.1130382,0.01660386,0.00003480367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009027167,0.0005339559,0.9664901,0.001704991,0.00005451027,0.0003743813,0.0007924672,0.0003187725,0.02070371],"genre_scores_gemma":[0.3977885,0.001105012,0.583988,0.000292303,0.0001377297,0.001294557,0.001086613,0.00008629316,0.01422102],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06492324,"threshold_uncertainty_score":0.1290907,"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."}}