{"id":"W2123738787","doi":"10.1190/1.1487299","title":"Joint inversion of gravity and magnetic data under lithologic constraints","year":2001,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mira Geoscience (Canada)","funders":"","keywords":"Lithology; Inversion (geology); Geology; Inference; Joint (building); Identification (biology); Computer science; Data mining; Geophysics; Data science; Seismology; Artificial intelligence; Petrology; Tectonics; Engineering","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":[0.0009451336,0.0007124996,0.0007203151,0.0009085984,0.0003199205,0.001207205,0.0006523976,0.0005614755,0.0007515871],"category_scores_gemma":[0.004742534,0.0004741595,0.0004594248,0.001457513,0.0007352792,0.001633482,0.001403214,0.0006898758,0.0005007851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002340733,"about_ca_system_score_gemma":0.001359565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005839985,"about_ca_topic_score_gemma":0.009814279,"domain_scores_codex":[0.999575,0.00009932319,0.00002365657,0.00007876151,0.0001332528,0.0000899833],"domain_scores_gemma":[0.999175,0.0002236764,0.0001367918,0.0001974609,0.0002019213,0.00006516677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009057987,0.0002815976,0.02752176,0.0002092897,0.0003414553,0.0002895523,0.0005031855,0.3800216,0.09347163,0.01448203,0.003328382,0.4786437],"study_design_scores_gemma":[0.0001109114,0.000101316,0.01039871,0.00001237545,0.00007835873,0.0001101085,0.0001418501,0.9585839,0.01738747,0.01068647,0.002351094,0.00003745218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3294098,0.0003543722,0.6646115,0.0004155331,0.0001182727,0.00004499327,0.0003777793,0.001598391,0.003069419],"genre_scores_gemma":[0.8640598,0.0002396296,0.1329349,0.00004753958,0.0001054436,0.00003370215,0.0007965167,0.0001062708,0.001676092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005839985,"threshold_uncertainty_score":0.01161194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08876944344066329,"score_gpt":0.2793829574587631,"score_spread":0.1906135140180998,"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."}}