{"id":"W2321928777","doi":"10.1190/1.3255552","title":"Prestack rank‐reducing noise suppression: Theory","year":2009,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Alberta","keywords":"Prestack; Rank (graph theory); Noise (video); Computer science; Noise measurement; Algorithm; Speech recognition; Noise reduction; Mathematics; Artificial intelligence; Geology; Combinatorics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001785272,0.001097281,0.000815216,0.001276711,0.0007055905,0.001500713,0.001116802,0.001190044,0.003689332],"category_scores_gemma":[0.005531854,0.0005579905,0.0006135885,0.001500784,0.003010642,0.002366279,0.001806245,0.002195438,0.00194278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007247619,"about_ca_system_score_gemma":0.0008191695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009555203,"about_ca_topic_score_gemma":0.0009406933,"domain_scores_codex":[0.9988258,0.0002878642,0.00004405325,0.0001426133,0.0005992811,0.0001002756],"domain_scores_gemma":[0.9969667,0.001959823,0.0002568268,0.0002742951,0.0004661147,0.00007628743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008953753,0.00006524918,0.000322625,0.0003494484,0.00005455299,0.0001261254,0.0002752852,0.1136346,0.008192074,0.6969867,0.01088831,0.1690156],"study_design_scores_gemma":[0.00002019445,0.00008488576,0.0002156849,0.0000777211,0.00001974168,0.0002632548,0.00006749977,0.6013686,0.005739185,0.3804111,0.01166615,0.00006585004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002310391,0.00111048,0.9904029,0.0002626689,0.00005639163,0.00001667495,0.00004068138,0.0001227129,0.00567702],"genre_scores_gemma":[0.3392817,0.009702343,0.6227559,0.001175821,0.001364871,0.0004877528,0.0004981675,0.0004090839,0.0243244],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003689332,"threshold_uncertainty_score":0.01234198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01355579922091375,"score_gpt":0.2739510818119579,"score_spread":0.2603952825910441,"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."}}