{"id":"W2625718541","doi":"","title":"Statistical Modeling Techniques In the Design And Operation of Pipeline Systems","year":2002,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Pipeline (software); Computer science; Statistical model; Artificial intelligence","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":[0.004222592,0.001088893,0.001298568,0.001138556,0.0005296049,0.001157077,0.001239316,0.0008688705,0.001241505],"category_scores_gemma":[0.00991792,0.001437969,0.001283864,0.001548026,0.0008962648,0.001525101,0.0008559721,0.001936154,0.0004116489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001010849,"about_ca_system_score_gemma":0.002658643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005179202,"about_ca_topic_score_gemma":0.005258761,"domain_scores_codex":[0.9970624,0.001789246,0.0001332772,0.0001850134,0.0007216911,0.0001083581],"domain_scores_gemma":[0.9946088,0.00425345,0.0003456308,0.0002002267,0.0005365892,0.00005524091],"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":[0.00004340644,0.00003036535,0.0003259683,0.00009118867,0.00007710844,0.0000202814,0.00003575498,0.9119461,0.0007617926,0.04189428,0.0006831217,0.0440906],"study_design_scores_gemma":[0.00001085588,0.00002806339,0.0001208744,0.0000105152,0.00001520506,0.000008102762,0.000005636011,0.9755701,0.0003934778,0.02255089,0.001277912,0.000008300628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002216821,0.0005451052,0.9964528,0.0001447381,0.00002685886,0.00001468865,0.00001986427,0.0001399365,0.000439258],"genre_scores_gemma":[0.4089445,0.004863638,0.5808827,0.0002230434,0.00041817,0.000539713,0.0003200963,0.000394332,0.003413833],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005179202,"threshold_uncertainty_score":0.02233142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02246886172067147,"score_gpt":0.2156656324463746,"score_spread":0.1931967707257032,"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."}}