{"id":"W3094154459","doi":"","title":"Using DAS for reflection seismology - lessons learned from three field studies","year":2017,"lang":"en","type":"article","venue":"eSpace (Curtin University)","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reflection (computer programming); Field (mathematics); Geology; Seismology; Computer science; Mathematics","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":[0.01998259,0.001384035,0.001107101,0.002003043,0.001229728,0.004140929,0.00374507,0.002451757,0.002778247],"category_scores_gemma":[0.01314513,0.0003940282,0.0008111213,0.001652439,0.00450822,0.006230004,0.003659586,0.003674279,0.001169168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002977673,"about_ca_system_score_gemma":0.002954656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01235064,"about_ca_topic_score_gemma":0.01385972,"domain_scores_codex":[0.9943874,0.002951037,0.0004025761,0.0008216803,0.001075394,0.0003617937],"domain_scores_gemma":[0.9759847,0.01189522,0.0007067649,0.002841071,0.007151622,0.001420586],"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":[0.0005522114,0.001689394,0.01740177,0.0009539201,0.00006504243,0.0008512192,0.004708022,0.003080572,0.007588943,0.01736634,0.01044977,0.9352927],"study_design_scores_gemma":[0.000579269,0.01037657,0.06520752,0.006091202,0.0003668595,0.004243039,0.0470765,0.01583766,0.05880919,0.1385769,0.6519643,0.000870902],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4206948,0.1408199,0.1632165,0.1548805,0.002690831,0.001152306,0.00112505,0.001278142,0.1141419],"genre_scores_gemma":[0.6620154,0.111751,0.1860791,0.01296462,0.001659847,0.0005644027,0.0007108062,0.0005634615,0.02369146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01998259,"threshold_uncertainty_score":0.1056793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2249319633750788,"score_gpt":0.3675356637742263,"score_spread":0.1426037003991474,"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."}}