{"id":"W2387705247","doi":"","title":"Issues in PetroChina's management of pipeline failure data and corresponding solutions","year":2014,"lang":"en","type":"article","venue":"Oil & Gas Storage and Transportation","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline transport; Incentive; China; Pipeline (software); Fossil fuel; Engineering; Petroleum industry; Forensic engineering; Waste management; Environmental engineering; Economics; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001166495,0.00008215691,0.0001107143,0.0001154273,0.00002349569,0.0000093804,0.0000734943,0.0000422614,0.000002705059],"category_scores_gemma":[0.000004448581,0.00008592173,0.000008320829,0.0001118373,0.00002154269,0.0001224227,0.000007566325,0.00007804343,4.887913e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006270532,"about_ca_system_score_gemma":0.000001143196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002515958,"about_ca_topic_score_gemma":0.0002127065,"domain_scores_codex":[0.9995719,0.000004814151,0.000133578,0.0001232146,0.00006051058,0.0001060204],"domain_scores_gemma":[0.9997829,0.00001631204,0.00001506053,0.0001606256,0.000007230168,0.00001789464],"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":[0.000080078,0.0001187034,0.01832212,0.004204846,0.0001731178,0.0001081988,0.004494424,0.08922916,0.007248232,0.02329538,0.001371646,0.8513541],"study_design_scores_gemma":[0.002467891,0.0001597469,0.2911496,0.001159656,0.0002789202,0.00001219738,0.004053957,0.6559113,0.002595649,0.001698476,0.03961481,0.0008977681],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9578009,0.001640215,0.03984663,0.0001184435,0.00007736707,0.00003249642,0.00003677781,0.0001873709,0.0002597446],"genre_scores_gemma":[0.9936936,0.001446871,0.004640635,0.000001382575,0.00001252982,0.00000466575,0.000119136,0.00001115456,0.00006996842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8504564,"threshold_uncertainty_score":0.3503787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00921924212160959,"score_gpt":0.2116884067474021,"score_spread":0.2024691646257925,"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."}}