{"id":"W2032785235","doi":"10.1115/pvp2012-78392","title":"Technical Basis for Code Case N-806, Evaluation of Metal Loss in Class 2 and 3 Metallic Piping Buried in a Back-Filled Trench","year":2012,"lang":"en","type":"article","venue":"Volume 1: Codes and Standards","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kinectrics (Canada)","funders":"","keywords":"Piping; Trench; Code (set theory); Scope (computer science); Section (typography); Key (lock); Class (philosophy); Computer science; Structural engineering; Engineering; Forensic engineering; Mechanical engineering; Materials science; Programming language; Artificial intelligence; Operating system","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":[0.003343359,0.0001781295,0.0004118985,0.000229917,0.00003825319,0.00002235007,0.00006109891,0.000124601,0.00003364683],"category_scores_gemma":[0.0006229521,0.0001759596,0.00004708763,0.00025514,0.0001088389,0.0002061157,0.00004539817,0.0001457802,1.670699e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003491354,"about_ca_system_score_gemma":0.00006408355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001659152,"about_ca_topic_score_gemma":0.0008905915,"domain_scores_codex":[0.9986601,0.0001001737,0.0003792789,0.0001987632,0.0003668238,0.000294853],"domain_scores_gemma":[0.9993224,0.0001648299,0.0000579168,0.0001599439,0.0002225364,0.00007233084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0014763,0.001010235,0.5063301,0.005105406,0.0008903804,0.0002754,0.01169677,0.001491095,0.2854187,0.04819224,0.002605776,0.1355076],"study_design_scores_gemma":[0.02004134,0.001724435,0.1700812,0.002158311,0.001798174,0.00288041,0.001757814,0.6606352,0.0465764,0.08278392,0.00593746,0.003625373],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839142,0.001296344,0.01282379,0.00002668429,0.00004631342,0.0005863248,0.0003237909,0.0001031537,0.0008794202],"genre_scores_gemma":[0.9310352,0.00006251656,0.06871495,0.000003199833,0.0000255932,0.000120519,0.000007200339,0.00002727961,0.000003593926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6591441,"threshold_uncertainty_score":0.7175425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0355164627523175,"score_gpt":0.3142308825494377,"score_spread":0.2787144197971201,"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."}}