{"id":"W4410111538","doi":"10.1029/2024jb030712","title":"Mapping Crustal Vp/Vs in North America With a Machine Learning Approach","year":2025,"lang":"en","type":"article","venue":"Journal of Geophysical Research Solid Earth","topic":"High-pressure geophysics and materials","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geology; Artificial intelligence; Computer science","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":[0.0003212509,0.0005227042,0.0002220479,0.002063575,0.0002923049,0.0005182481,0.0004462684,0.0003157516,0.0006705962],"category_scores_gemma":[0.0009434763,0.0002414684,0.0003638468,0.002264176,0.0002089235,0.0003776235,0.0004249602,0.0002939487,0.0001588025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001132815,"about_ca_system_score_gemma":0.0008965177,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2348574,"about_ca_topic_score_gemma":0.2576618,"domain_scores_codex":[0.9998945,0.00002357226,0.000005699983,0.00004221103,0.00001838399,0.00001566752],"domain_scores_gemma":[0.9996799,0.00009051617,0.00006470231,0.00003332979,0.0001102035,0.00002130789],"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":[0.00009207606,0.0001026106,0.3195271,0.00006052124,0.0002252893,0.0002390914,0.0002182584,0.4701203,0.00507497,0.0004969022,0.002724,0.2011189],"study_design_scores_gemma":[0.00000677232,0.00001287231,0.1484058,0.0000169265,0.00001975868,0.00002983039,0.0001909938,0.8489313,0.000702356,0.0006506563,0.001015652,0.00001716442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98386,0.0004257668,0.01223204,0.0002162731,0.00001000621,0.00001607106,0.001226791,0.0004765816,0.001536494],"genre_scores_gemma":[0.987659,0.0001226956,0.01049992,0.00001657614,0.000007278106,0.00001014929,0.00127826,0.00001504308,0.0003910005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7651426,"threshold_uncertainty_score":0.4669807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02244884239106559,"score_gpt":0.2818794233719912,"score_spread":0.2594305809809256,"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."}}