{"id":"W3124153908","doi":"10.1115/ipc2020-9452","title":"Pipeline Geohazards Screening: Using Results of Flood Scour Assessments to Provide a Simple Screening Tool for Pipeline Watercourse Crossings for Western Canada","year":2020,"lang":"en","type":"article","venue":"Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Flood myth; Channel (broadcasting); Rating curve; Pipeline (software); Hydrology (agriculture); Return period; Fluvial; Environmental science; Current (fluid); Civil engineering; Geology; Geotechnical engineering; Engineering; Geography; Geomorphology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006344728,0.0002436002,0.0004260628,0.00003294698,0.0005716708,0.0002026866,0.0001307481,0.00008544474,0.00003271543],"category_scores_gemma":[0.0001835361,0.0002181525,0.00003473328,0.00008865015,0.00009094409,0.0004568985,0.0001029298,0.00006974002,5.305217e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003634207,"about_ca_system_score_gemma":0.0001075206,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03394131,"about_ca_topic_score_gemma":0.007108177,"domain_scores_codex":[0.998095,0.00003431323,0.0006926153,0.0005260095,0.0002065593,0.0004454924],"domain_scores_gemma":[0.9993999,0.0000426308,0.000158109,0.0001298445,0.00009078888,0.0001787408],"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":[0.004440133,0.0001799319,0.2795567,0.001087141,0.0001634684,0.00002953892,0.005865815,0.07783195,0.5936755,0.00002548495,0.01040774,0.02673661],"study_design_scores_gemma":[0.01829404,0.00260746,0.04958134,0.001551278,0.0006810973,0.00005168916,0.003386996,0.2302662,0.425149,0.00007475509,0.2657951,0.002561039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8448653,0.00004864837,0.1526201,0.001052439,0.0002143262,0.0007084759,0.0004556293,0.00002626819,0.000008806971],"genre_scores_gemma":[0.9429598,0.00002800038,0.05541697,0.0004780072,0.0003707055,0.00009877602,0.000105393,0.00003068553,0.0005116738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2553874,"threshold_uncertainty_score":0.9724917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03333109606085773,"score_gpt":0.2893410823235792,"score_spread":0.2560099862627215,"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."}}