{"id":"W2332685471","doi":"10.3968/7932","title":"The In-Situ Stress Analysis of Casing Damage Wells in the Sixth Middle District Based on Kriging Interpolation Method","year":2016,"lang":"en","type":"article","venue":"Advances in petroleum exploration and development","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Casing; Stress (linguistics); Interpolation (computer graphics); Geotechnical engineering; Geology; Structural engineering; Shrinkage; Hydraulic fracturing; Kriging; Engineering; Petroleum engineering; Mathematics; Mechanical engineering; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005990944,0.000106816,0.0001786218,0.0004676995,0.00005909023,0.00003331251,0.0001147982,0.00002972084,0.000004688812],"category_scores_gemma":[0.00005019824,0.00005699206,0.00003204023,0.0006396957,0.00002220639,0.0002720208,0.00001364044,0.00009392372,0.000001060046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001108439,"about_ca_system_score_gemma":0.00001965362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002743675,"about_ca_topic_score_gemma":0.003245645,"domain_scores_codex":[0.9990209,0.0001316251,0.0003620138,0.0001464127,0.0001926174,0.0001464024],"domain_scores_gemma":[0.9992496,0.0004968731,0.00006504448,0.0001547108,0.00001445567,0.00001925685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001983808,0.0000195998,0.01141705,0.00001804358,0.00002924695,0.000002785328,0.001487189,0.9524155,0.0001220102,0.00003183568,0.000002235147,0.03443464],"study_design_scores_gemma":[0.00044715,0.00001551252,0.03257399,0.0002045944,0.00002541867,1.523364e-7,0.002591264,0.9570851,0.003950304,0.00007970133,0.00288895,0.0001379076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1698685,0.0005993912,0.8266208,0.000558173,0.00009440367,0.0001113754,0.000003834244,0.00002532668,0.002118163],"genre_scores_gemma":[0.9973838,0.0006059896,0.001904037,0.00003015375,0.00000767938,0.00003169019,0.0000152374,0.000005988901,0.00001540972],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8275153,"threshold_uncertainty_score":0.2324069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01424605181394246,"score_gpt":0.2624476735434046,"score_spread":0.2482016217294622,"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."}}