{"id":"W4413303424","doi":"10.21203/rs.3.rs-7313707/v1","title":"Global machine-learning detection of submarine calderas","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Bộ Giáo dục và Ðào tạo; Ministry of Education, India; Ministry of Education - Singapore","keywords":"Caldera; Submarine; Geology; Artificial intelligence; Computer science; Seismology; Oceanography; Volcano","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":[0.0004136123,0.0006975622,0.0007211077,0.002205961,0.0006097087,0.0009263848,0.0008304869,0.001245269,0.002414841],"category_scores_gemma":[0.001948768,0.0002953936,0.0004494896,0.0009871202,0.0003908329,0.0007391266,0.001008893,0.001055851,0.00142441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000442975,"about_ca_system_score_gemma":0.0004311533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005316006,"about_ca_topic_score_gemma":0.01366445,"domain_scores_codex":[0.9996401,0.00003162978,0.000009522865,0.0001436023,0.00008939384,0.00008576703],"domain_scores_gemma":[0.9990343,0.0001603674,0.0001445598,0.0002004738,0.0003819491,0.00007841591],"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":[0.000731357,0.0002288704,0.1929021,0.0002368593,0.0002171202,0.001180455,0.0006886616,0.1404783,0.101707,0.009214414,0.01724979,0.5351651],"study_design_scores_gemma":[0.0000239106,0.0001189898,0.09707812,0.00004760359,0.00007361605,0.0004781928,0.0004661923,0.8610728,0.02635642,0.006261481,0.00798285,0.00003988345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7899028,0.0006869817,0.1936492,0.0004617828,0.0001836002,0.00007575656,0.001415326,0.002332059,0.01129254],"genre_scores_gemma":[0.9731286,0.00007046109,0.02272326,0.0000413272,0.000033911,0.00001434289,0.0009951026,0.0001265539,0.002866517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005316006,"threshold_uncertainty_score":0.01057017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02747210932646487,"score_gpt":0.3428227707385667,"score_spread":0.3153506614121018,"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."}}