{"id":"W2972430975","doi":"10.1190/gem2019-047.1","title":"Modelling the subseafloor structure of seafloor massive sulphide deposits using surface geometry magnetic inversion","year":2019,"lang":"en","type":"article","venue":"","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Geology; Seafloor spreading; Inversion (geology); Geometry; Magnetic anomaly; Geophysics; Surface (topology); Seismology; Tectonics; Mathematics","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":[0.00008827548,0.0003040643,0.0001753984,0.0004297403,0.0001390786,0.000595813,0.0005074868,0.0004766942,0.001195041],"category_scores_gemma":[0.0003899541,0.0002450597,0.0003378585,0.0003715044,0.0002633495,0.0002436307,0.000247834,0.00017349,0.0002124615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004628755,"about_ca_system_score_gemma":0.0005756477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05585229,"about_ca_topic_score_gemma":0.04538898,"domain_scores_codex":[0.9999672,0.000006510717,0.000001476992,0.000008843207,0.000005812041,0.00001017013],"domain_scores_gemma":[0.9999231,0.00002726995,0.00001302926,0.000008023522,0.00001692966,0.00001166344],"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":[0.00003150941,0.00001374582,0.007863637,0.000009768826,0.00001437471,0.00008430411,0.00003183071,0.9854271,0.001848142,0.0005155277,0.0001423327,0.004017808],"study_design_scores_gemma":[0.00000532455,0.000004736977,0.001973033,0.000001372327,0.000002570527,0.000007985623,0.00001470942,0.9974908,0.0001587473,0.0001930804,0.0001447959,0.000002851971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9241607,0.000102618,0.06824049,0.0001258135,0.00001655074,0.00002656302,0.0007164904,0.0005170953,0.006093715],"genre_scores_gemma":[0.9914084,0.00003886856,0.007175076,0.000008293086,0.000004232875,0.000007254691,0.0002295235,0.00002977423,0.001098472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05585229,"threshold_uncertainty_score":0.1110544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01608056786235663,"score_gpt":0.2154219463054881,"score_spread":0.1993413784431314,"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."}}