{"id":"W1963915844","doi":"10.1190/1.2821941","title":"Improving AVO fidelity by NMO stretching and offset-dependent tuning corrections","year":2007,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"ARC Resources (Canada)","funders":"","keywords":"Offset (computer science); Fidelity; High fidelity; Materials science; Geology; Computer science; Physics; Acoustics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001154105,0.00009491556,0.00009395719,0.00005996119,0.0005002295,0.00008657424,0.0001563527,0.00004431492,0.00009564911],"category_scores_gemma":[0.00007956699,0.00006883775,0.00002669057,0.0001063523,0.00008797061,0.0001818902,0.00002126069,0.0002849511,0.00006549742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001133239,"about_ca_system_score_gemma":0.00001471682,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008240568,"about_ca_topic_score_gemma":0.0002167886,"domain_scores_codex":[0.9992204,0.0000501377,0.000152495,0.0001793994,0.0001347592,0.0002628432],"domain_scores_gemma":[0.9994312,0.0002594488,0.00006623919,0.0001507775,0.00001886409,0.00007347605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001610797,0.000008645472,0.08829533,0.00001617203,0.00001212406,0.000005076659,0.001239968,0.00005603881,0.002745974,0.00004703352,0.05656137,0.8509961],"study_design_scores_gemma":[0.0009463183,0.0003596516,0.06320802,0.0002302478,0.0001366673,0.0002598887,0.009906398,0.6761398,0.05722189,0.003522272,0.1867035,0.001365302],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9632403,0.000758447,0.014092,0.0007982676,0.0007651446,0.0001289711,0.0000231885,0.0003107722,0.01988295],"genre_scores_gemma":[0.9969162,0.00003244223,0.0004346537,0.001133572,0.0001145385,2.95419e-7,0.00001714484,0.000003295597,0.001347804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8496308,"threshold_uncertainty_score":0.9983636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322394228729701,"score_gpt":0.2314967113272673,"score_spread":0.2182727690399703,"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."}}