{"id":"W2039615356","doi":"10.1190/1.1444898","title":"Past, present, and future of geophysical inversion—A new millennium analysis","year":2001,"lang":"en","type":"article","venue":"Geophysics","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Interpreter; Inversion (geology); Computer science; Geophysics; Inference; Inverse problem; Inverse theory; Geology; Algorithm; Artificial intelligence; Seismology; Mathematics; Programming language","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":[0.00008082914,0.0001939903,0.0004328902,0.0001142555,0.00009838384,0.00002711245,0.0002109068,0.00009064636,0.000523415],"category_scores_gemma":[0.000006024279,0.0001507598,0.0002282023,0.001858116,0.0001003493,0.0001651047,0.00003378992,0.0001913322,0.0001212268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002015399,"about_ca_system_score_gemma":0.00003115815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004653515,"about_ca_topic_score_gemma":0.00007622064,"domain_scores_codex":[0.9986085,0.00009802348,0.0002238172,0.0003597906,0.0003337042,0.0003761915],"domain_scores_gemma":[0.9990347,0.0002149275,0.0001041351,0.0002782133,0.00005757586,0.0003104747],"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":[0.00009617255,0.0000819155,0.0772227,0.0000189823,0.0002628722,0.00001032518,0.000167079,0.0003209006,0.00009428013,0.0003715421,0.004285614,0.9170676],"study_design_scores_gemma":[0.0002946737,0.0002353196,0.9068239,0.000003257991,0.0003144107,0.00000207133,0.00006451645,0.007901937,0.0001277695,0.01345263,0.07055531,0.0002242457],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909071,0.001065334,0.0008709538,0.002323031,0.0002281246,0.0001428742,0.00003709389,0.00004590505,0.004379601],"genre_scores_gemma":[0.990056,0.0005404484,0.002618929,0.0002958637,0.00463127,8.545255e-7,0.00009326803,0.000006048902,0.001757313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9168434,"threshold_uncertainty_score":0.7034754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192002668575244,"score_gpt":0.2235479666413839,"score_spread":0.2116279399556314,"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."}}