{"id":"W2016022280","doi":"10.1103/physreve.79.011902","title":"<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:mrow><mml:mn>1</mml:mn><mml:mo>∕</mml:mo><mml:msup><mml:mi>f</mml:mi><mml:mi>α</mml:mi></mml:msup></mml:mrow></mml:math>noise in reaction times: A proposed model based on Piéron’s law and information processing","year":2009,"lang":"lv","type":"article","venue":"Physical Review E","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia; Universidad de Granada; University of Toronto","keywords":"Algorithm; Brownian motion; Noise (video); Artificial intelligence; Power function; Computer science; Physics; Mathematics; Mathematical analysis; Quantum mechanics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005286288,0.001096905,0.0007037414,0.001463345,0.0004097295,0.00290872,0.001908628,0.00150295,0.4545989],"category_scores_gemma":[0.002099381,0.0004621157,0.0007487643,0.002223932,0.0005930269,0.002427862,0.0009156212,0.001247371,0.2857996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0012536,"about_ca_system_score_gemma":0.0007631308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003829066,"about_ca_topic_score_gemma":0.002923066,"domain_scores_codex":[0.9997903,0.00003919471,0.00001339599,0.00003925366,0.00009872021,0.00001925469],"domain_scores_gemma":[0.9994579,0.0001826713,0.00005673148,0.0001047906,0.0001555998,0.00004230663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006487197,0.00004060471,0.0001612308,0.0004767244,0.00001787255,0.0000914441,0.00007740478,0.001457985,0.001767173,0.09901007,0.7483879,0.1484467],"study_design_scores_gemma":[0.00003268489,0.00002280755,0.0007588397,0.0001095728,0.000007507416,0.0001755251,0.00003485905,0.008793133,0.002401199,0.06225991,0.9253752,0.00002888578],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.003057609,0.004846074,0.1976128,0.009747412,0.002279822,0.0002806415,0.01943965,0.02755178,0.7351842],"genre_scores_gemma":[0.04593934,0.01030558,0.09887584,0.001914908,0.001060538,0.0008704638,0.02485704,0.01768539,0.7984909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4545989,"threshold_uncertainty_score":0.7779485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01757709476170093,"score_gpt":0.2537159431734418,"score_spread":0.2361388484117408,"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."}}