{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01524738,0.0003510508,0.0005475169,0.004636665,0.002817976,0.009632911,0.004898581,0.001738259,0.002300266],"category_scores_gemma":[0.02866131,0.0006132322,0.0003932214,0.01173637,0.002065714,0.01332595,0.005721915,0.001821461,0.000889551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006295389,"about_ca_system_score_gemma":0.0172545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07070435,"about_ca_topic_score_gemma":0.03632274,"domain_scores_codex":[0.9896497,0.002627487,0.002097108,0.001950934,0.002719925,0.000954915],"domain_scores_gemma":[0.9637123,0.008185091,0.004438993,0.01174067,0.01025934,0.001663551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003964567,0.0001545281,0.1202166,0.00118387,0.0001180712,0.001909272,0.01737315,0.01190994,0.005402524,0.145263,0.04117827,0.6548943],"study_design_scores_gemma":[0.00007255613,0.0001980929,0.08549969,0.002149172,0.0001069693,0.002495772,0.04050936,0.05630814,0.01275059,0.07647231,0.7230458,0.0003916081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3903677,0.01202852,0.3284372,0.1457851,0.000930214,0.001355269,0.01364297,0.005674564,0.1017785],"genre_scores_gemma":[0.8839643,0.002975252,0.09645876,0.001580851,0.0001432016,0.0003322491,0.004646154,0.0002201422,0.009679196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07070435,"threshold_uncertainty_score":0.1405856,"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."}}