{"id":"W3124889144","doi":"10.1306/08192019051","title":"Applying deep learning for identifying bioturbation from core photographs","year":2021,"lang":"en","type":"article","venue":"AAPG Bulletin","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Bioturbation; Geology; Core (optical fiber); Paleontology; Artificial intelligence; Computer science","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":[0.0002020041,0.0001367116,0.0001662544,0.00007852999,0.0001072246,0.00008656487,0.00008695672,0.0001015691,0.0004005439],"category_scores_gemma":[0.0002252327,0.000160103,0.0001055299,0.0001970735,0.000008709585,0.00003814209,0.00002216227,0.0001930378,0.00004767986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002985357,"about_ca_system_score_gemma":0.000005479562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001924234,"about_ca_topic_score_gemma":0.00000427403,"domain_scores_codex":[0.9991953,0.00003177613,0.0002178787,0.0002057467,0.0001306114,0.0002187049],"domain_scores_gemma":[0.9993137,0.00035148,0.00002880231,0.0001753,0.00007089425,0.00005984387],"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":[0.000005605195,0.000005971793,0.0006666449,0.00008126254,0.00005028645,0.000005844879,0.0002781503,0.9482335,0.03729473,0.00007832974,0.0006739843,0.01262572],"study_design_scores_gemma":[0.0006119478,0.000009898926,0.0009386488,0.00006616788,0.00002604346,0.000002573202,0.0002690807,0.7268506,0.02232619,0.0005040467,0.2481273,0.0002675011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1918486,0.001937688,0.8036905,0.00004331083,0.0005632153,0.0002428559,0.000005660711,0.0005323825,0.001135768],"genre_scores_gemma":[0.8402342,0.0001493641,0.1582833,0.00004374384,0.0002385164,0.0002250935,0.0002146108,0.00007194927,0.0005392167],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6483855,"threshold_uncertainty_score":0.6528811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03382580312968813,"score_gpt":0.2809625588656054,"score_spread":0.2471367557359173,"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."}}