{"id":"W2086933291","doi":"10.1121/1.429338","title":"Regularized matched-mode processing for source localization","year":2000,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Replica; Computer science; Grid; Modal; A priori and a posteriori; Underdetermined system; Inverse problem; Algorithm; Inversion (geology); Point source; Signal processing; Acoustics; Mathematics; Mathematical analysis; Physics; Optics; Telecommunications; Geometry","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":[0.0008286487,0.000593313,0.0004298614,0.0004989433,0.0002039597,0.0004884986,0.0006799588,0.000640696,0.001997477],"category_scores_gemma":[0.002541138,0.0002544457,0.0004995627,0.0005387759,0.0004551614,0.001049331,0.0007433894,0.0007765145,0.0008064129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00030191,"about_ca_system_score_gemma":0.0004378394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007813572,"about_ca_topic_score_gemma":0.0008659406,"domain_scores_codex":[0.9995149,0.0001698125,0.00001897805,0.00008257324,0.0001881658,0.00002564634],"domain_scores_gemma":[0.999334,0.0003305584,0.00006088054,0.0001346335,0.0001256039,0.00001427847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000317496,0.0001037539,0.0005774187,0.0001879582,0.0001081922,0.000139313,0.0001366822,0.4679281,0.07403695,0.07005317,0.002901457,0.3835096],"study_design_scores_gemma":[0.00001477882,0.00003608497,0.0001168552,0.000009718642,0.000009131719,0.00004698672,0.000009536522,0.9720744,0.01021819,0.01453111,0.002918211,0.00001499111],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002624555,0.00007122683,0.9964498,0.00004053412,0.00001776766,0.00001188094,0.00002433689,0.0001912993,0.0005685792],"genre_scores_gemma":[0.09801684,0.0002127437,0.9000828,0.00007792642,0.00006156145,0.00008256732,0.0001505907,0.00009010403,0.001224971],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001997477,"threshold_uncertainty_score":0.006682217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0155036024468692,"score_gpt":0.2645345207437213,"score_spread":0.2490309182968521,"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."}}