{"id":"W2943754646","doi":"10.1190/tle38050374.1","title":"Thermal effective stress in shales","year":2019,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"OPKO Health (Canada); Petro-Canada","funders":"","keywords":"Oil shale; Scaling; Thermal; Effective stress; Thermal expansion; Stress (linguistics); Geology; Pore water pressure; Core (optical fiber); Matrix (chemical analysis); Geomechanics; Calibration; Mechanics; Geotechnical engineering; Materials science; Geometry; Mathematics; Thermodynamics; Composite material; Physics; Statistics","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":[0.0005654506,0.0003187414,0.0001878247,0.001022454,0.0002250901,0.0005622915,0.0004043092,0.0002393607,0.0006849963],"category_scores_gemma":[0.001251763,0.0001862618,0.00009500137,0.0005628813,0.0006518317,0.000773849,0.0003220853,0.0002350592,0.0001027592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004306948,"about_ca_system_score_gemma":0.0003531637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002981458,"about_ca_topic_score_gemma":0.006571714,"domain_scores_codex":[0.9997904,0.00002567213,0.00001563579,0.0000542355,0.00008770583,0.00002644246],"domain_scores_gemma":[0.9996308,0.00008249615,0.00008406719,0.00004602379,0.0001308041,0.00002576437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002102416,0.0001389279,0.09149993,0.0001801183,0.00005144875,0.000489086,0.0006275457,0.2702733,0.5418398,0.007988143,0.0003344075,0.08636706],"study_design_scores_gemma":[0.0000185043,0.0003624004,0.2147956,0.00004664129,0.00002221636,0.0002470372,0.0005355359,0.5786839,0.1976106,0.005567213,0.002027574,0.00008260151],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9716498,0.0001752594,0.02678672,0.00003979208,0.000008682025,0.00001187621,0.00009003343,0.00008213766,0.001155717],"genre_scores_gemma":[0.9982288,0.00004075986,0.001476135,0.000004436933,0.000001701907,0.000005005286,0.00003838507,0.00000528013,0.0001995113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002981458,"threshold_uncertainty_score":0.005928218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042318259907888,"score_gpt":0.2206116596007027,"score_spread":0.2101884770016238,"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."}}