{"id":"W2328327771","doi":"10.3997/1365-2397.2014013","title":"Reservoir characterization of the Montney Shale – integrating seismic inversion with microseismic","year":2014,"lang":"en","type":"article","venue":"First Break","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geology; Microseism; Oil shale; Hydraulic fracturing; Petrology; Lithology; Unconventional oil; Seismic inversion; Reservoir modeling; Inversion (geology); Well logging; Petroleum engineering; Seismology; Tectonics; Paleontology","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":[0.0002111679,0.0001112484,0.0001279978,0.00006166262,0.0002233756,0.000031578,0.0003080649,0.0000542519,0.0001722538],"category_scores_gemma":[0.00004072742,0.00006651873,0.00004587707,0.0002367015,0.0001172366,0.000202374,0.00002503091,0.0001361221,0.00003997205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007048463,"about_ca_system_score_gemma":0.00002762991,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007268409,"about_ca_topic_score_gemma":0.000189749,"domain_scores_codex":[0.9992228,0.00007214064,0.0001654032,0.0001831103,0.0001900795,0.0001665239],"domain_scores_gemma":[0.9994164,0.00005751806,0.0001510346,0.0002765381,0.0000544308,0.00004405438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001491609,0.00004670905,0.8836825,0.0001709003,0.00002848917,0.000002413552,0.00193533,0.001140747,0.01290752,0.00008123655,0.01908892,0.08076604],"study_design_scores_gemma":[0.0004539691,0.0002356007,0.29727,0.0004333403,0.00002413491,0.00003157755,0.0002204629,0.4680928,0.05685372,0.0003544066,0.1757463,0.0002836453],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914314,0.0000156377,0.001510389,0.002066531,0.0001543227,0.000133933,0.00004183216,0.00007507859,0.004570874],"genre_scores_gemma":[0.9967782,0.00001346834,0.0004794421,0.001795534,0.00004921672,9.514615e-7,0.0001038039,0.000005066361,0.0007743142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5864125,"threshold_uncertainty_score":0.9993423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006882737374619339,"score_gpt":0.1736790495479881,"score_spread":0.1667963121733688,"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."}}