{"id":"W2944658541","doi":"10.48550/arxiv.1905.04307","title":"Semantic Segmentation of Seismic Images","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Segmentation; Geology; Computer science; Artificial intelligence; Seismology; Computer vision","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":[0.0004804934,0.001351425,0.000812011,0.003710636,0.0004708278,0.001507033,0.001005496,0.001228299,0.003028301],"category_scores_gemma":[0.001588622,0.0004666892,0.001144041,0.002559216,0.0009979222,0.001660803,0.001681839,0.001009127,0.001606675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001363057,"about_ca_system_score_gemma":0.001593026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009222676,"about_ca_topic_score_gemma":0.01571596,"domain_scores_codex":[0.999314,0.00008196459,0.00003977999,0.0002498443,0.0001806904,0.000133742],"domain_scores_gemma":[0.9995059,0.00009485048,0.0000668375,0.00015533,0.000143126,0.00003394348],"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":[0.000823548,0.0001860939,0.004857352,0.0004843728,0.0001489323,0.0003429335,0.0005703283,0.1448435,0.0953222,0.02363775,0.01406415,0.7147189],"study_design_scores_gemma":[0.00003015117,0.0001104679,0.005730826,0.0001083267,0.00006863281,0.0003123627,0.0006061661,0.8460358,0.07732537,0.04209113,0.02753231,0.00004848542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08233234,0.0006795861,0.8961262,0.0004085792,0.0001198819,0.0001913094,0.003590346,0.007761236,0.008790449],"genre_scores_gemma":[0.446431,0.0008538266,0.5320269,0.0002662323,0.0001089008,0.0001584425,0.01481885,0.0009263676,0.00440942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009222676,"threshold_uncertainty_score":0.01833802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0405388137518825,"score_gpt":0.1787244981219414,"score_spread":0.1381856843700589,"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."}}