{"id":"W3127074056","doi":"10.1190/tle40020140.1","title":"Geophysical electromagnetics: A retrospective, DISC 2017, and a look forward","year":2021,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Electromagnetics; Visibility; Relevance (law); Geophysics; Perspective (graphical); Software; Computer science; Exploration geophysics; Data science; Engineering; Political science; Geography; Geology; Engineering physics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001802416,0.0001248862,0.0002124598,0.00002094418,0.0002096283,0.00008556847,0.0001567184,0.00004645482,0.0002862856],"category_scores_gemma":[0.000171022,0.0000773071,0.00007194171,0.000347219,0.0001321061,0.00007810227,0.00002706843,0.0002924677,0.0006159973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004429814,"about_ca_system_score_gemma":0.00003074429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001427332,"about_ca_topic_score_gemma":0.0001609922,"domain_scores_codex":[0.9988889,0.0001546785,0.0001110948,0.0002897165,0.0001759479,0.0003796355],"domain_scores_gemma":[0.9992492,0.0003556835,0.0000327355,0.000209016,0.00003734685,0.0001159828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001453565,0.0001705321,0.09383991,0.00006668294,0.0001424872,0.0001562875,0.001135334,0.00003843129,0.009250034,0.01604394,0.01566167,0.8633493],"study_design_scores_gemma":[0.0002150712,0.000397791,0.8823473,0.00001182464,0.0000445472,0.00005352808,0.00003437394,0.003498699,0.001813803,0.1019689,0.009406968,0.0002071582],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662797,0.001344016,0.0004981591,0.002969329,0.0002155723,0.0001149847,0.00001366439,0.00005867358,0.02850583],"genre_scores_gemma":[0.989781,0.00007903914,0.001133596,0.00047064,0.0003738246,0.0000016558,0.0000107427,0.000003955709,0.00814553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8631422,"threshold_uncertainty_score":0.7917604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013287960622419,"score_gpt":0.239774765808654,"score_spread":0.226486805186235,"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."}}