{"id":"W2187021041","doi":"","title":"Challenges in AVO Compliant Processing of Multiple Surveys","year":2009,"lang":"en","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geology; Data processing; Residual; Inversion (geology); Weighting; Seismology; Signal processing; Attenuation; Algorithm; Computer science; Acoustics; Telecommunications","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":[0.02626889,0.0008279056,0.001283746,0.001432041,0.001783941,0.005093909,0.003039996,0.002337878,0.002787188],"category_scores_gemma":[0.04961139,0.00117389,0.0006833281,0.001820566,0.001750413,0.004807489,0.004119715,0.002640643,0.002857636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008165046,"about_ca_system_score_gemma":0.002710335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004456386,"about_ca_topic_score_gemma":0.003184719,"domain_scores_codex":[0.9865469,0.005129637,0.00110671,0.001403338,0.005043958,0.0007695388],"domain_scores_gemma":[0.9586597,0.01325325,0.001944107,0.01068627,0.01485196,0.0006045942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005260293,0.0001188818,0.008629871,0.000688624,0.0002148425,0.0007411725,0.002517038,0.06560567,0.05258716,0.03624573,0.02740524,0.8047197],"study_design_scores_gemma":[0.0002759741,0.0003212558,0.02012022,0.0008509031,0.0001492375,0.002363206,0.005090272,0.5474243,0.05637382,0.1542241,0.2123908,0.00041587],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02517861,0.0006581167,0.9574186,0.004457297,0.0004575789,0.0002088699,0.0003249864,0.004628493,0.006667445],"genre_scores_gemma":[0.2126076,0.0004701522,0.7795778,0.001402152,0.0004635081,0.0004535871,0.0009804791,0.001404078,0.002640759],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02626889,"threshold_uncertainty_score":0.1389248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0762815826193729,"score_gpt":0.2604514016943846,"score_spread":0.1841698190750117,"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."}}