{"id":"W1999580741","doi":"10.2118/166922-ms","title":"Case Studies: E-line ‘Heavy’ Workovers in High Latitude Environments","year":2013,"lang":"en","type":"article","venue":"SPE Arctic and Extreme Environments Technical Conference and Exhibition","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Debris; Marine engineering; Computer science; Line (geometry); Lift (data mining); Drilling; On board; Environmental science; Engineering; Mechanical engineering; Geology; Aerospace engineering; Oceanography","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":[0.0000816266,0.0002095892,0.0002247356,0.00009080074,0.00005574199,0.00003144184,0.00006025119,0.0001485417,0.00008478783],"category_scores_gemma":[0.00002871593,0.0001956765,0.00002150231,0.0000733646,0.000193411,0.0002382222,0.00009101389,0.0002619083,0.00003934912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009493645,"about_ca_system_score_gemma":0.000001802616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005267556,"about_ca_topic_score_gemma":0.00002165732,"domain_scores_codex":[0.9990803,0.00001224398,0.0002391588,0.0002726192,0.0001200927,0.0002755588],"domain_scores_gemma":[0.9996547,0.00004846594,0.00002357533,0.0001906733,0.000002765468,0.00007989491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001562881,0.001303475,0.08401554,0.001463717,0.0008292243,0.003675418,0.002355099,0.05888516,0.2038118,0.01741116,0.002414196,0.623679],"study_design_scores_gemma":[0.0162938,0.003282971,0.548543,0.003723412,0.0007607213,0.005639504,0.01260091,0.1526886,0.04416985,0.1905315,0.01250946,0.009256362],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907047,0.000536475,0.007877426,0.0002343283,0.00006171448,0.0002512511,0.000003516707,0.000165012,0.0001655505],"genre_scores_gemma":[0.9922674,0.004798096,0.002710631,0.00003220552,0.00002191695,0.00007036674,0.000009308024,0.00001925803,0.00007086726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6144226,"threshold_uncertainty_score":0.7979458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02861011224693743,"score_gpt":0.2191306241127275,"score_spread":0.1905205118657901,"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."}}