{"id":"W2891478434","doi":"10.1190/segam2018-2997973.1","title":"Egypt West Kalabsha 3D broadband ultrahigh density seismic survey","year":2018,"lang":"en","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Apache (Canada)","funders":"","keywords":"Seismic survey; Broadband; Geology; Seismology; Archaeology; Geological survey; Telecommunications; Geography; Engineering; Paleontology","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":[0.0001858669,0.0002611425,0.0001983214,0.0007061182,0.0003777353,0.0003762396,0.0002041767,0.0002818564,0.01009166],"category_scores_gemma":[0.0002381501,0.0001895538,0.00009209869,0.0008493545,0.0001707951,0.0003159585,0.0005478739,0.0003508225,0.003382097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004116608,"about_ca_system_score_gemma":0.001027679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01206984,"about_ca_topic_score_gemma":0.02982839,"domain_scores_codex":[0.9998709,0.00001054739,0.00000539426,0.0000181501,0.00006878056,0.00002620056],"domain_scores_gemma":[0.9998285,0.000007917634,0.00001637051,0.00001943086,0.0001116705,0.000016142],"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":[0.001462819,0.00025514,0.1139518,0.0007976241,0.0001270221,0.003550255,0.002299979,0.008379031,0.2401385,0.006875973,0.1005772,0.5215846],"study_design_scores_gemma":[0.00008333039,0.0001856939,0.5408551,0.0001271549,0.00005167222,0.001498498,0.001806607,0.008121217,0.02670712,0.0007593967,0.419724,0.00008026012],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7574461,0.0007819085,0.02112159,0.0017161,0.0002399704,0.0003384035,0.03032671,0.001141893,0.1868872],"genre_scores_gemma":[0.8590832,0.001217342,0.02961444,0.0005092659,0.0001191922,0.0001874541,0.02020538,0.0001902784,0.08887339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01206984,"threshold_uncertainty_score":0.03375995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861162476033228,"score_gpt":0.2243236871840793,"score_spread":0.205712062423747,"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."}}