{"id":"W2614837433","doi":"10.5006/c2011-11301","title":"ILI Performance- Validating Rupture Pressure Prediction Performance of In-Line Inspection Tools","year":2011,"lang":"en","type":"article","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Computer science; Line (geometry); Reliability engineering; Engineering; Forensic engineering","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":[0.007176128,0.000827932,0.0004941466,0.001499587,0.0002934979,0.001240836,0.001867001,0.0008745648,0.002375932],"category_scores_gemma":[0.01526164,0.0003955633,0.0004746841,0.0008394148,0.0003826463,0.001241326,0.0007748876,0.0006589916,0.001589332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007515319,"about_ca_system_score_gemma":0.0005011705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003131317,"about_ca_topic_score_gemma":0.002339606,"domain_scores_codex":[0.9958214,0.001122913,0.0004304168,0.0005400443,0.001822621,0.0002627017],"domain_scores_gemma":[0.9830762,0.004764223,0.002198024,0.003213133,0.006465469,0.0002828931],"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":[0.002698338,0.00142081,0.2380687,0.0009044905,0.0003050881,0.000401454,0.001265245,0.2609211,0.2385687,0.001452963,0.005935085,0.2480581],"study_design_scores_gemma":[0.00006885194,0.002155005,0.0614405,0.00007286208,0.00008679595,0.0002290677,0.0003237881,0.6501691,0.2821514,0.0002293065,0.002988534,0.00008467438],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7661222,0.0001344422,0.2123338,0.0001705983,0.00007243025,0.0002532715,0.001570612,0.0133185,0.006024032],"genre_scores_gemma":[0.9601719,0.00003411447,0.03723763,0.00004629866,0.00000744315,0.00006010997,0.001116577,0.0001925468,0.001133435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007176128,"threshold_uncertainty_score":0.03795147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929845242711609,"score_gpt":0.1965280602400183,"score_spread":0.1772296078129023,"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."}}