{"id":"W4400810668","doi":"10.1109/tgrs.2024.3431439","title":"5-D Seismic Data Interpolation by Continuous Representation","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Interpolation (computer graphics); Computer science; Representation (politics); Geology; Nearest-neighbor interpolation; Multivariate interpolation; Bilinear interpolation; Remote sensing; Artificial intelligence; Computer vision","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":[0.0007868673,0.0005735939,0.000465223,0.0006027814,0.000186577,0.0008658985,0.001129349,0.0008392683,0.002215079],"category_scores_gemma":[0.002959091,0.0004032831,0.0006370404,0.0009158917,0.0006569752,0.001932659,0.001435618,0.001334393,0.0008911811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003738632,"about_ca_system_score_gemma":0.0006942922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002061325,"about_ca_topic_score_gemma":0.002163723,"domain_scores_codex":[0.9996425,0.00008941434,0.00002413719,0.00007230423,0.0001323477,0.00003917561],"domain_scores_gemma":[0.99939,0.0002088546,0.00007102493,0.0001841995,0.0001182787,0.00002764478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002023313,0.00006252044,0.001469273,0.0001575634,0.00004151851,0.0001274481,0.0001855422,0.6691971,0.02246425,0.03540001,0.002296554,0.2683959],"study_design_scores_gemma":[0.000004285258,0.00001772295,0.0001268323,0.000008897087,0.000002952288,0.0000295145,0.00001369322,0.9900128,0.003006742,0.005537227,0.001231839,0.000007491999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009003443,0.00005467714,0.989827,0.00008710584,0.00001570823,0.0000097343,0.00007075984,0.0004114799,0.0005200772],"genre_scores_gemma":[0.3207338,0.0002933984,0.6758566,0.0001052802,0.0000351898,0.00008294716,0.0006976387,0.0001473826,0.002047721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002215079,"threshold_uncertainty_score":0.007410228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0243971494365471,"score_gpt":0.2627799499593745,"score_spread":0.2383828005228274,"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."}}