{"id":"W4313559442","doi":"10.3389/feart.2022.1020384","title":"The improvement of sparsity gravity inversion using an adaptive lanczos bidiagonalization method","year":2023,"lang":"en","type":"article","venue":"Frontiers in Earth Science","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lanczos resampling; Inversion (geology); Inverse problem; Algorithm; Computer science; Applied mathematics; Mathematical optimization; Mathematics; Physics; Geology; Eigenvalues and eigenvectors; Mathematical analysis","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":[0.0004201873,0.0006590516,0.0005932734,0.0004934187,0.0004169797,0.0006042755,0.0008889739,0.0005905143,0.003684914],"category_scores_gemma":[0.001392338,0.0003220362,0.0006863326,0.000570335,0.0004325275,0.0008971787,0.0007003293,0.0009980425,0.001464204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003876982,"about_ca_system_score_gemma":0.001226443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00824742,"about_ca_topic_score_gemma":0.008279769,"domain_scores_codex":[0.9994828,0.00009010845,0.00003318318,0.00007647033,0.0002789382,0.00003848989],"domain_scores_gemma":[0.9995406,0.00008575538,0.00003900305,0.00005480467,0.0002552275,0.00002468643],"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":[0.0003294792,0.0001423647,0.003476262,0.0008247347,0.0001356335,0.0004195904,0.00055117,0.2450939,0.1287419,0.04269389,0.01918237,0.5584087],"study_design_scores_gemma":[0.00005284774,0.00005928942,0.0005320697,0.00002333802,0.00002314858,0.000134984,0.00004331048,0.9747313,0.009035317,0.003439059,0.01189505,0.0000301898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006593116,0.0002501782,0.9894888,0.0001435905,0.00007541378,0.00004206261,0.00004310068,0.0005558863,0.002807861],"genre_scores_gemma":[0.1298226,0.0005831099,0.8619249,0.0001959921,0.0001055978,0.0001589358,0.0003347152,0.0003288033,0.006545295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00824742,"threshold_uncertainty_score":0.01639885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03252638183701639,"score_gpt":0.277774226929063,"score_spread":0.2452478450920466,"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."}}