{"id":"W3185524196","doi":"","title":"Multi-scale Modelling of the Superior Craton, Canada using a Sequential Inversion Workflow of Magnetotelluric Data","year":2020,"lang":"en","type":"article","venue":"Japan Geoscience Union","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Magnetotellurics; Workflow; Geology; Inversion (geology); Craton; Scale (ratio); Seismology; Geophysics; Geodesy; Computer science; Database; Cartography; Geography; Engineering; Electrical resistivity and conductivity","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":[0.0001927361,0.001040535,0.0006039022,0.0009616595,0.001273825,0.001934538,0.001537162,0.000885759,0.003541896],"category_scores_gemma":[0.0006671564,0.0007427156,0.0008911352,0.001865046,0.0005568901,0.0006576257,0.0008214415,0.0007921454,0.0006680765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00552526,"about_ca_system_score_gemma":0.02197608,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9621505,"about_ca_topic_score_gemma":0.9629552,"domain_scores_codex":[0.9997916,0.000008860216,0.000009050689,0.00005959458,0.00007829564,0.00005263709],"domain_scores_gemma":[0.999777,0.00002124685,0.00001601957,0.0000212904,0.0001276177,0.00003679426],"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":[0.00006711542,0.00004758106,0.01079354,0.00006446577,0.0001200566,0.0001704464,0.0001260362,0.9633004,0.005473052,0.001249097,0.003024269,0.01556391],"study_design_scores_gemma":[0.00002983129,0.000007630618,0.008241104,0.00001479858,0.00003673828,0.00001849656,0.0001101146,0.9871889,0.001037091,0.0004492393,0.002827938,0.00003811015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7478513,0.001063789,0.1824982,0.001301894,0.0003157965,0.000279965,0.0188086,0.008969936,0.03891057],"genre_scores_gemma":[0.9473037,0.0003111677,0.0407759,0.00008503551,0.00002008214,0.00005564307,0.004139558,0.0004665825,0.006842368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03784955,"threshold_uncertainty_score":0.07614481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0819806705857333,"score_gpt":0.2397757079012834,"score_spread":0.1577950373155501,"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."}}