{"id":"W2906785942","doi":"10.1190/tle38010035.1","title":"A high-density, high-resolution joint 3D VSP–3D surface seismic case study in the Canadian oil sands","year":2019,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Virtual Materials Group (Canada); Ambrose University; Canadian Bio-Systems (Canada); D-Wave Systems (Canada)","funders":"Suncor Energy Incorporated","keywords":"Geology; Vertical seismic profile; Seismology; Anisotropy; Inversion (geology); Azimuth; Joint (building); Seismic inversion; Attenuation; Geophysical imaging; Data processing; Seismic survey; Seismic tomography; Mineralogy; Oil sands; Petrology; Geophysics; Geometry; Mantle (geology); Optics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001599167,0.0001568058,0.0001971211,0.0001340823,0.0004653774,0.0001454016,0.0003817776,0.00006997356,0.0002628764],"category_scores_gemma":[0.00003029958,0.00009496593,0.00003917811,0.0003262518,0.00009129942,0.0001509681,0.00002367136,0.00041593,0.001067206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005500071,"about_ca_system_score_gemma":0.0001202467,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9245926,"about_ca_topic_score_gemma":0.5000376,"domain_scores_codex":[0.9985113,0.0003528684,0.0001946497,0.000263285,0.0002580882,0.0004198425],"domain_scores_gemma":[0.9991968,0.0001689378,0.00006610122,0.0004530844,0.00003046447,0.00008465719],"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":[0.0001101063,0.0001986958,0.568302,0.00008663231,0.0001059184,0.003606043,0.04127896,0.03423336,0.0002088275,0.0002349876,0.2010935,0.150541],"study_design_scores_gemma":[0.003307329,0.001497799,0.3259571,0.0003169788,0.000226587,0.004702119,0.02656144,0.556399,0.001246328,0.00178821,0.07614072,0.001856307],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908198,0.0001089426,0.00002266561,0.003391677,0.0006629523,0.0002444514,0.00001695913,0.00008469255,0.004647851],"genre_scores_gemma":[0.9942729,0.00001350704,0.0001854896,0.003553707,0.0001032845,0.000001376157,0.0000215461,0.000006160652,0.001841954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5221657,"threshold_uncertainty_score":0.9997106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02545383123443305,"score_gpt":0.2296138376987181,"score_spread":0.2041600064642851,"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."}}