{"id":"W2106968045","doi":"10.1190/1.2235616","title":"Regularization and datuming of seismic data by weighted, damped least squares","year":2006,"lang":"en","type":"article","venue":"Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Regularization (linguistics); Extrapolation; Hessian matrix; Algorithm; Synthetic data; Diagonal; Mathematics; Applied mathematics; Computer science; Mathematical optimization; Mathematical analysis; Geometry; Artificial intelligence","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":[0.001615883,0.0007691632,0.0006107978,0.0007093195,0.0003104406,0.0007207188,0.000797472,0.0005599719,0.0009188959],"category_scores_gemma":[0.003500522,0.0004013004,0.0005611556,0.0008054079,0.0007469318,0.001004715,0.001130276,0.0008847792,0.000335643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004201981,"about_ca_system_score_gemma":0.0007731753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002404498,"about_ca_topic_score_gemma":0.003590842,"domain_scores_codex":[0.9991862,0.0002900315,0.00005089481,0.0001280245,0.000296801,0.00004800699],"domain_scores_gemma":[0.9986874,0.0006216889,0.0001535615,0.0002774441,0.0002215013,0.00003830866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002892411,0.0001394987,0.001739272,0.0001700577,0.0001421963,0.0001008742,0.0002415519,0.5520486,0.1485606,0.01505727,0.001392732,0.2801182],"study_design_scores_gemma":[0.000006788736,0.00002720982,0.000379674,0.000003905822,0.000006547756,0.00002519698,0.00001286297,0.9844438,0.0127,0.001613718,0.0007686156,0.0000116877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01793654,0.00003221755,0.9815222,0.00003399073,0.000008682026,0.00001535592,0.00002027924,0.0002561827,0.0001745013],"genre_scores_gemma":[0.1402505,0.00005850368,0.8583402,0.00004536465,0.00001404225,0.00005663767,0.000165899,0.0001318065,0.0009370141],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002404498,"threshold_uncertainty_score":0.008545697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009256770261599238,"score_gpt":0.1945160682326795,"score_spread":0.1852592979710802,"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."}}