{"id":"W4406903841","doi":"10.1190/geo2024-0502.1","title":"From shallow to deep: Enhancing seismic resolution with weak supervision","year":2025,"lang":"en","type":"article","venue":"Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Geology; Seismology; Resolution (logic); Seismic exploration; Computer science; Artificial intelligence","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":[0.00009539125,0.0001117459,0.0001239707,0.00007935546,0.0001548527,0.00005174671,0.0001811826,0.00004372375,0.0001890661],"category_scores_gemma":[0.0000140202,0.00009123502,0.00003300995,0.0003327657,0.00003002417,0.0001759665,0.00002068707,0.0001156489,0.0003939403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009815682,"about_ca_system_score_gemma":0.00004724881,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02043635,"about_ca_topic_score_gemma":0.000451726,"domain_scores_codex":[0.999194,0.00003221922,0.0001173092,0.0002669271,0.0001697681,0.0002197946],"domain_scores_gemma":[0.999569,0.00006563223,0.00002605889,0.0002334782,0.00004227163,0.00006353868],"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":[0.0002473192,0.00005186,0.04198078,0.00004501384,0.00006028945,0.00001490375,0.001606346,0.0085751,0.003159881,0.0002852262,0.04813193,0.8958414],"study_design_scores_gemma":[0.0008974434,0.000566431,0.1865037,0.000704122,0.00009555413,0.000004297089,0.002520827,0.5256574,0.03617108,0.03336517,0.2126066,0.0009074667],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9044853,0.0001916724,0.07877503,0.001725331,0.0003496292,0.000164283,0.00003271358,0.0002355601,0.0140405],"genre_scores_gemma":[0.9867644,0.00001862161,0.007742246,0.00429598,0.0001205779,0.000001448264,0.0001248851,0.000003359145,0.0009285179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8949339,"threshold_uncertainty_score":0.9860867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005995171366150657,"score_gpt":0.2017584975002262,"score_spread":0.1957633261340755,"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."}}