{"id":"W4392166782","doi":"10.3390/min14030237","title":"Inversion for 3D Conductivity and Chargeability Models Using EM Data Acquired by the New Airborne TargetEM System in Ontario, Canada","year":2024,"lang":"en","type":"article","venue":"Minerals","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inversion (geology); Offset (computer science); Computer science; Geology; Transmitter; Remote sensing; Conductivity; Physics; Telecommunications; Seismology","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":[0.0001999763,0.0002945878,0.0001748075,0.0004613096,0.0005499335,0.0003905316,0.0005016524,0.0002343976,0.001002407],"category_scores_gemma":[0.0007226759,0.0001629729,0.0002794938,0.0007181889,0.0002578962,0.0004074731,0.0003784733,0.0003033283,0.0001886389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00446774,"about_ca_system_score_gemma":0.006263791,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8772787,"about_ca_topic_score_gemma":0.9369016,"domain_scores_codex":[0.9998587,0.000009915228,0.000003630949,0.00002162525,0.00008112429,0.00002493496],"domain_scores_gemma":[0.9998496,0.00001799994,0.00001120897,0.000008444532,0.0001008371,0.00001196976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000449691,0.0001638397,0.1930729,0.0003069265,0.0001495787,0.0009035469,0.00143532,0.4608061,0.1017079,0.008681225,0.01244492,0.219878],"study_design_scores_gemma":[0.00008408808,0.000047744,0.1251925,0.00003060644,0.00004674064,0.0001353887,0.0007392113,0.8424237,0.01421778,0.00121518,0.01580117,0.00006579285],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9007149,0.0002537257,0.07226844,0.0005430424,0.00003148587,0.00007997741,0.003001076,0.001010116,0.02209727],"genre_scores_gemma":[0.9631159,0.0001264697,0.03099024,0.00004798756,0.000005605952,0.00001982338,0.001412772,0.00006944594,0.004211656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1227213,"threshold_uncertainty_score":0.246888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06855847821004041,"score_gpt":0.2540915569259142,"score_spread":0.1855330787158738,"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."}}