{"id":"W132522011","doi":"","title":"Managing Pipeline Corrosion Control with Information Flow on the Internet","year":2000,"lang":"en","type":"article","venue":"","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Society of Intestinal Research","funders":"","keywords":"Corrosion; Pipeline (software); The Internet; Flow control (data); Control (management); Flow (mathematics); Petroleum engineering; Information flow; Forensic engineering; Computer science; Environmental science; Materials science; Engineering; World Wide Web; Metallurgy; Telecommunications; Mechanical engineering; Physics; Artificial intelligence; Mechanics","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":[0.002231566,0.000890334,0.0009522612,0.002572204,0.001047448,0.00384268,0.001714698,0.001551924,0.005640405],"category_scores_gemma":[0.006095701,0.0005064966,0.0004156721,0.001886343,0.0006488994,0.005674365,0.001316876,0.001293417,0.001165489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215064,"about_ca_system_score_gemma":0.001433529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006893159,"about_ca_topic_score_gemma":0.006544258,"domain_scores_codex":[0.9988569,0.0003244281,0.00008922461,0.0001640261,0.000382094,0.0001833466],"domain_scores_gemma":[0.9952785,0.002431642,0.0004076024,0.0006306853,0.001030197,0.0002214735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001530416,0.001664794,0.008323872,0.0002293435,0.0001507624,0.0005842144,0.0004838824,0.3489724,0.016162,0.02563666,0.03213303,0.5641286],"study_design_scores_gemma":[0.0001152245,0.0001391462,0.001633073,0.00002374949,0.00009502287,0.00007703557,0.000197451,0.9555086,0.008589179,0.02074445,0.01283142,0.00004563959],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3587804,0.002264476,0.5049818,0.006556933,0.0006218283,0.0006608725,0.0008466209,0.01340515,0.111882],"genre_scores_gemma":[0.9724824,0.000354997,0.02002178,0.0002040169,0.000157032,0.0000609091,0.00033604,0.0001928863,0.006189882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006893159,"threshold_uncertainty_score":0.0188691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003018046954733871,"score_gpt":0.1432651986389439,"score_spread":0.1402471516842101,"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."}}