{"id":"W1969968601","doi":"10.1167/9.9.4","title":"Scale dependence and channel switching in letter identification","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"National Eye Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Channel (broadcasting); Computer science; Contrast (vision); Speech recognition; Acoustics; Physics; Artificial intelligence; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003524349,0.0001217141,0.0002019634,0.0002564261,0.0002654927,0.0006036262,0.0002914462,0.0003391053,0.00176412],"category_scores_gemma":[0.003304539,0.0002682068,0.0001779556,0.0001361132,0.0005981526,0.0009296731,0.0005002641,0.0006890912,0.0002929092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003091484,"about_ca_system_score_gemma":0.0001465363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004217516,"about_ca_topic_score_gemma":0.0003822059,"domain_scores_codex":[0.9997028,0.0000522565,0.00001523303,0.00008198866,0.00009192703,0.00005584453],"domain_scores_gemma":[0.9975951,0.001252157,0.0003804848,0.0003796512,0.0001876344,0.0002049655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004990243,0.00007798783,0.004038167,0.00003475453,0.000008170417,0.000115628,0.0001597881,0.0007157061,0.9802207,0.002260405,0.0001944752,0.01167519],"study_design_scores_gemma":[0.0001049771,0.000414718,0.2119606,0.00001879899,0.00005427019,0.001163949,0.0002521352,0.05534795,0.7138339,0.01428359,0.002424932,0.0001401536],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916818,0.000193708,0.005907925,0.0000791416,0.00002580751,0.00001127913,0.00003601675,0.0000940399,0.001970301],"genre_scores_gemma":[0.9985222,0.00005514478,0.001009404,0.00003111285,0.00001018344,0.000007000837,0.00003108032,0.0000234294,0.0003104298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00176412,"threshold_uncertainty_score":0.005901575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03677375726422834,"score_gpt":0.3444264972145292,"score_spread":0.3076527399503008,"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."}}