{"id":"W2092798840","doi":"10.3997/2214-4609.20141164","title":"A Comparison of Different Scaling Methods for Least-squares Migration/inversion","year":2014,"lang":"en","type":"article","venue":"Proceedings","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Hessian matrix; Rate of convergence; Diagonal; Least-squares function approximation; Applied mathematics; Mathematics; Block matrix; Identity matrix; Inversion (geology); Quasi-Newton method; Mathematical optimization; Precondition; Inverse; Diagonal matrix; Algorithm; Newton's method; Computer science; Nonlinear system; Eigenvalues and eigenvectors; Estimator; Statistics; Physics; Geometry; Geology","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":[0.0004066976,0.00009167126,0.0001952578,0.00009409674,0.0001141873,0.00003410213,0.0001428117,0.00004728377,0.00008796943],"category_scores_gemma":[0.0001742226,0.00007099813,0.00006571449,0.00009261277,0.00005293001,0.000142064,0.000009034176,0.00006627277,0.00000687178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000346339,"about_ca_system_score_gemma":0.000006042643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000359945,"about_ca_topic_score_gemma":0.000004773689,"domain_scores_codex":[0.9993428,0.00001587844,0.0002001781,0.0001686561,0.0001195039,0.0001529727],"domain_scores_gemma":[0.9995214,0.0001455637,0.0001249262,0.00004809518,0.0001043234,0.00005567267],"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":[0.00005346367,0.00002616544,0.3417791,0.0001588026,0.0000087012,1.08292e-8,0.001100663,0.00001667852,0.004418862,0.0004988867,0.01470573,0.637233],"study_design_scores_gemma":[0.0001973964,0.0002487066,0.007724313,0.00006264394,0.00002196761,8.111998e-7,0.0007335223,0.7509028,0.1887412,0.004519008,0.04672114,0.0001264561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8663641,0.000243804,0.1264362,0.001192822,0.0002532957,0.0002955871,0.000008141334,0.0001849844,0.005021097],"genre_scores_gemma":[0.9263137,0.00001034756,0.07323421,0.0002861996,0.00005622968,0.000002397773,0.00001875222,0.000002932518,0.00007521192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7508862,"threshold_uncertainty_score":0.289522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03640842101793222,"score_gpt":0.331699847603097,"score_spread":0.2952914265851647,"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."}}