{"id":"W2024142454","doi":"10.1016/j.visres.2005.08.016","title":"Noise masking reveals channels for second-order letters","year":2005,"lang":"en","type":"article","venue":"Vision Research","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Eye Institute; National Institutes of Health","keywords":"Luminance; Channel (broadcasting); Spatial frequency; Noise (video); Masking (illustration); Speech recognition; Computer science; Physics; Optics; Artificial intelligence; Telecommunications; Image (mathematics); Art","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001802204,0.0001150086,0.0001326362,0.0003403551,0.0006251219,0.0002885229,0.0003801553,0.0000828213,0.002596639],"category_scores_gemma":[0.0009448187,0.0001006412,0.00005909888,0.0006370948,0.0001063394,0.0003007902,0.0001321742,0.000320372,0.001100496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005898235,"about_ca_system_score_gemma":0.0000446319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000280566,"about_ca_topic_score_gemma":0.000003223358,"domain_scores_codex":[0.9976452,0.0002738413,0.0002195767,0.0005214741,0.0007350907,0.0006048057],"domain_scores_gemma":[0.9988833,0.000469497,0.00004192429,0.000269211,0.0001717673,0.0001642911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005014805,0.00005837671,0.000003096361,0.00004324684,7.101211e-7,0.00000265337,0.0004151804,0.00007636107,0.9497253,0.000978148,0.02253889,0.02610791],"study_design_scores_gemma":[0.0008046384,0.0003156603,0.00007232112,0.00009785224,0.000001765615,0.00001131233,0.0001369986,0.01620618,0.7522015,0.002503321,0.2274078,0.0002406872],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9412284,0.00004860466,0.03071301,0.01966321,0.0005782459,0.001103549,0.00002611047,0.0002101097,0.006428724],"genre_scores_gemma":[0.9783868,0.00001847939,0.002434438,0.005199495,0.0004465893,0.00008556669,0.000003173094,0.00003405067,0.01339139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2048689,"threshold_uncertainty_score":0.9996772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1957727390868548,"score_gpt":0.4713596190127693,"score_spread":0.2755868799259145,"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."}}