{"id":"W2999175271","doi":"10.1061/9780784481660.023","title":"Transmission Pipeline Route Analysis to Support Growing Water Demand","year":2018,"lang":"en","type":"article","venue":"Pipelines 2018","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Pipeline transport; Quarter (Canadian coin); Engineering; Operations research; Computer science; Geography; Environmental engineering; Mechanical engineering; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001302389,0.0009005578,0.0003761728,0.002732683,0.0009112682,0.002342166,0.001213505,0.0005836825,0.0135018],"category_scores_gemma":[0.004988171,0.0004545721,0.001195994,0.002650868,0.0003560698,0.002645796,0.0008610898,0.0009395222,0.001696926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002752434,"about_ca_system_score_gemma":0.003071248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04926195,"about_ca_topic_score_gemma":0.07890953,"domain_scores_codex":[0.998965,0.0002949871,0.00005180081,0.0002173924,0.0003543915,0.0001164474],"domain_scores_gemma":[0.998042,0.0005603723,0.0001652466,0.0001497975,0.001014368,0.00006815094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002891343,0.000260023,0.03135774,0.0004725499,0.0001563059,0.0007939757,0.001206853,0.6884971,0.005738501,0.0483161,0.01957109,0.2033406],"study_design_scores_gemma":[0.00002859124,0.000169205,0.004845597,0.00007598244,0.0000692088,0.0001478492,0.002070649,0.9476518,0.0038788,0.01151803,0.0294879,0.00005643548],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2069041,0.0003278466,0.708191,0.001485244,0.0001739117,0.0008748557,0.006832093,0.00488419,0.0703267],"genre_scores_gemma":[0.6359596,0.0004613435,0.3341833,0.0001100795,0.00004748847,0.0003006354,0.006288498,0.0007383808,0.02191074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04926195,"threshold_uncertainty_score":0.09795046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008925045363902883,"score_gpt":0.2275289125103228,"score_spread":0.2186038671464199,"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."}}