{"id":"W1992743151","doi":"10.1115/ipc2002-27310","title":"An Innovative Approach for Pipeline Repairs","year":2002,"lang":"en","type":"article","venue":"4th International Pipeline Conference, Parts A and B","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Pipeline (software); Global Positioning System; Pipeline transport; Computer science; Database; Software; Quality (philosophy); Relational database; Engineering; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001021377,0.0001744959,0.0001684098,0.0001683406,0.00004342643,0.00007408615,0.0001995534,0.00009666349,0.00009750861],"category_scores_gemma":[0.00007581276,0.0001581287,0.00003162232,0.0001403166,0.00005795378,0.0001638166,0.0000259712,0.0001482192,0.000007040579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001897591,"about_ca_system_score_gemma":0.000005618142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003501896,"about_ca_topic_score_gemma":0.000002498275,"domain_scores_codex":[0.9992003,0.000005283222,0.0002477785,0.0002291985,0.0001241518,0.0001932176],"domain_scores_gemma":[0.9994851,0.00003178984,0.00003125445,0.0001664757,0.0002305201,0.0000548146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000974244,0.0008052982,0.00461855,0.0004100274,0.0004349671,0.00002669094,0.002462637,0.06444802,0.00528788,0.1869663,0.2314371,0.503005],"study_design_scores_gemma":[0.000348825,0.00005155808,0.0001424099,0.00001678709,0.00000723466,0.000009502402,0.0001133935,0.9057609,0.0009614282,0.0004306955,0.0919571,0.0002001011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05156343,0.0005247976,0.8796538,0.0007587426,0.001055758,0.0004212999,0.0001776109,0.001985756,0.06385884],"genre_scores_gemma":[0.9854112,0.0001398667,0.01212457,0.00004829351,0.0002837086,0.00007456978,0.0001415806,0.0000235807,0.001752662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9338477,"threshold_uncertainty_score":0.6448301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03266877056378333,"score_gpt":0.2449774683998987,"score_spread":0.2123086978361154,"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."}}