{"id":"W1983339420","doi":"10.2118/145402-pa","title":"Geomechanical-Data Acquisition, Monitoring, and Applications in SAGD","year":2011,"lang":"en","type":"article","venue":"Journal of Canadian Petroleum Technology","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geomechanics; Petroleum engineering; Instrumentation (computer programming); Geology; Reservoir simulation; Steam injection; Reservoir engineering; Oil field; Petroleum reservoir; Geotechnical engineering; Computer science; Petroleum","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":[0.0005613137,0.0003569004,0.0002392218,0.001340049,0.0003101788,0.0005362335,0.0005480549,0.0003242519,0.001708727],"category_scores_gemma":[0.00105404,0.0002222699,0.0001977859,0.001571687,0.0003353463,0.0003602303,0.000831945,0.0002585257,0.0003855353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007110491,"about_ca_system_score_gemma":0.001156053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02163634,"about_ca_topic_score_gemma":0.03584301,"domain_scores_codex":[0.9996482,0.00006652458,0.00002139611,0.00005253031,0.000178868,0.00003235641],"domain_scores_gemma":[0.9995795,0.00009415673,0.00003917456,0.0000679324,0.0001952992,0.00002390207],"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":[0.000183187,0.0001287792,0.02602203,0.0003946665,0.00002686205,0.0001814264,0.000420681,0.06794514,0.1087571,0.004426824,0.002225403,0.7892879],"study_design_scores_gemma":[0.00007441907,0.0004209212,0.09342104,0.0002233663,0.00008126849,0.0005323726,0.0008094428,0.6404727,0.1906167,0.00817906,0.06499798,0.000170778],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1595893,0.000451247,0.8231881,0.0003641992,0.0000448426,0.0003410253,0.00249092,0.004639414,0.008890944],"genre_scores_gemma":[0.6166086,0.0004513418,0.3797078,0.00006632855,0.00001381238,0.0001855255,0.001350032,0.0001033957,0.001513182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02163634,"threshold_uncertainty_score":0.04302078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02522034443354715,"score_gpt":0.2193976825487381,"score_spread":0.1941773381151909,"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."}}