{"id":"W2012070999","doi":"10.2118/142854-pa","title":"Assessing Well-Integrity Risk: A Qualitative Model","year":2012,"lang":"en","type":"article","venue":"SPE Drilling & Completion","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"ConocoPhillips (Canada)","funders":"ConocoPhillips","keywords":"Brainstorming; Failure mode and effects analysis; Risk analysis (engineering); Risk assessment; Ranking (information retrieval); Process (computing); Risk management; Computer science; Fault tree analysis; Containment (computer programming); Engineering; Reliability engineering; Business; Computer security","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":[0.005817841,0.0007829473,0.0003354943,0.001785754,0.002233306,0.005691671,0.003183795,0.001867883,0.01244904],"category_scores_gemma":[0.0115814,0.0005166794,0.001159945,0.00156947,0.004184463,0.005636855,0.002749761,0.001547316,0.0009759055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009958241,"about_ca_system_score_gemma":0.007402849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02383878,"about_ca_topic_score_gemma":0.01652268,"domain_scores_codex":[0.9960209,0.00230104,0.0001383439,0.000270597,0.0009516262,0.000317491],"domain_scores_gemma":[0.9884099,0.008056347,0.0006941062,0.0004982097,0.00197757,0.0003638433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007243425,0.0002096764,0.004553743,0.0005441757,0.00003460009,0.0005342625,0.01570125,0.1476635,0.001267163,0.803974,0.003742761,0.02170234],"study_design_scores_gemma":[0.00006103265,0.000214383,0.001797819,0.0007309979,0.00006933987,0.0003311808,0.03049984,0.4033871,0.001973351,0.4930913,0.06773371,0.0001099546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0934653,0.000346844,0.7127235,0.00953939,0.00008707778,0.001728755,0.002298843,0.0004372151,0.1793731],"genre_scores_gemma":[0.7835893,0.0005799296,0.1996127,0.0004258077,0.00001711029,0.001638137,0.0007422582,0.00009896175,0.01329582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02383878,"threshold_uncertainty_score":0.07225239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.343738488006651,"score_gpt":0.5000031668834591,"score_spread":0.1562646788768082,"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."}}