{"id":"W2019833113","doi":"10.1115/ipc2002-27233","title":"Probabilistic Modeling of Corroded Pipeline Structures","year":2002,"lang":"en","type":"article","venue":"4th International Pipeline Conference, Parts A and B","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; TransCanada (Canada); Martec (Canada)","funders":"","keywords":"Corrosion; Randomness; Pipeline (software); Pipeline transport; Probabilistic logic; Computer science; Random field; Field (mathematics); Structural engineering; Engineering; Materials science; Reliability engineering; Metallurgy; Mechanical engineering; Artificial intelligence; Mathematics; Statistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009058983,0.0001845805,0.0002806723,0.0001349893,0.00004623752,0.00005389357,0.0002036238,0.0001041878,0.00156203],"category_scores_gemma":[0.0001413865,0.0001478929,0.00008909198,0.0001131788,0.0001123012,0.000125324,0.00004160149,0.0002140045,0.00001161835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002229829,"about_ca_system_score_gemma":0.00000979197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000774486,"about_ca_topic_score_gemma":0.00007789179,"domain_scores_codex":[0.9988756,0.00001890291,0.0004682971,0.0002227512,0.0002474155,0.0001670924],"domain_scores_gemma":[0.999325,0.00004276201,0.0000578563,0.0001655232,0.0003297338,0.00007910834],"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":[0.00005724912,0.0001401923,0.001123603,0.0003432192,0.00024329,0.00001237499,0.00139721,0.8933588,0.00261862,0.0515467,0.009238598,0.03992021],"study_design_scores_gemma":[0.0002645231,0.00001710876,0.0001245851,0.00004617805,0.00004343388,0.00001286399,0.00008626281,0.9870621,0.0004052413,0.009866441,0.00190379,0.0001674959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8760291,0.001338642,0.07427294,0.001471779,0.001897519,0.0003719037,0.0002088628,0.0003102307,0.04409904],"genre_scores_gemma":[0.9976587,0.0003557598,0.0005803599,0.00005032521,0.0001864829,0.000007367808,0.0000457321,0.00001203155,0.001103186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1216297,"threshold_uncertainty_score":0.9993507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03718732399932575,"score_gpt":0.243853329915235,"score_spread":0.2066660059159092,"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."}}