{"id":"W183712856","doi":"10.5006/c2010-10062","title":"A 5-M Approach to Control External Pipeline Corrosion","year":2010,"lang":"en","type":"article","venue":"","topic":"Corrosion Behavior and Inhibition","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Corrosion; Pipeline (software); Control (management); Materials science; Computer science; Petroleum engineering; Metallurgy; Engineering; Artificial intelligence; Operating system","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":[0.0005829131,0.0007899691,0.0006289725,0.0006945497,0.0005855339,0.0011212,0.001705162,0.0008543867,0.006149584],"category_scores_gemma":[0.0006886015,0.000292793,0.0007801809,0.0002122645,0.0005457693,0.0008556328,0.002009498,0.0007988475,0.001739656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008585193,"about_ca_system_score_gemma":0.0008160935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004405842,"about_ca_topic_score_gemma":0.003932388,"domain_scores_codex":[0.9991486,0.000125531,0.00004348362,0.0002020101,0.0003805173,0.00009977277],"domain_scores_gemma":[0.9996087,0.00004668029,0.00007653249,0.00007964757,0.0001616254,0.00002692807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005664702,0.0004074906,0.003393963,0.0005946461,0.0001731589,0.0004750088,0.0004241845,0.3877459,0.1922521,0.05303114,0.006589903,0.354346],"study_design_scores_gemma":[0.00004468422,0.0007184875,0.001424565,0.00006009274,0.00006731191,0.0001220172,0.00008111069,0.9163417,0.03640658,0.006827868,0.03785195,0.0000536293],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0171646,0.000152425,0.9656326,0.000124032,0.0001038437,0.0001050986,0.00005915044,0.002052857,0.01460533],"genre_scores_gemma":[0.7372297,0.0001972571,0.2412266,0.0002439636,0.00007229854,0.0001843625,0.0001391203,0.000160001,0.02054666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006149584,"threshold_uncertainty_score":0.02057242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01278189795398054,"score_gpt":0.2508418889177045,"score_spread":0.2380599909637239,"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."}}