{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005138025,0.00006182087,0.00009905496,0.00004582998,0.00002738567,0.00003336676,0.00004541378,0.00003739267,0.000001801266],"category_scores_gemma":[0.00003786013,0.00004554283,0.000005897186,0.00006225345,0.000007502082,0.0001009727,0.000007000079,0.00005776477,9.943707e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001047898,"about_ca_system_score_gemma":0.000001196612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000978935,"about_ca_topic_score_gemma":0.000009293291,"domain_scores_codex":[0.999428,0.00008552949,0.0002391905,0.00007110218,0.00008609163,0.00009009604],"domain_scores_gemma":[0.9998053,0.00007126966,0.00001772997,0.0000595996,0.00003321026,0.00001288167],"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":[0.000001211253,0.000005621923,0.00006891037,0.00006909019,0.000001814239,0.00000126133,0.002336149,0.9956977,0.0002627717,0.0002217599,0.0004689808,0.0008647746],"study_design_scores_gemma":[0.00005790196,0.00001732715,0.000007470391,0.00009240495,0.000003535219,0.000005360097,0.0006373257,0.9985361,0.0005050363,0.00001425634,0.00007015252,0.00005308986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01173329,0.0006233776,0.9860579,0.00002192162,0.00005610255,0.0002307677,0.000005823762,0.00006244044,0.001208404],"genre_scores_gemma":[0.9842129,0.00005021601,0.01562262,0.000005350348,0.00005818416,0.00002085351,0.00000289697,0.00001028216,0.00001673696],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9724796,"threshold_uncertainty_score":0.1857183,"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."}}