{"id":"W2045027872","doi":"10.1167/5.8.477","title":"Noise does not shrink the summation region for grating detection","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Noise (video); Grating; Acoustics; Physics; Computer science; Optics; Artificial intelligence","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":[0.000731257,0.0007136579,0.0008108288,0.000361533,0.0004216161,0.000892176,0.0008576241,0.0012267,0.005856934],"category_scores_gemma":[0.004230075,0.0005453016,0.0005281503,0.0002756749,0.0006594593,0.00211947,0.00076411,0.001069405,0.00190695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004787655,"about_ca_system_score_gemma":0.0005398425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003998745,"about_ca_topic_score_gemma":0.0006673256,"domain_scores_codex":[0.9994434,0.00006582647,0.00002918526,0.000168345,0.0002107251,0.00008247644],"domain_scores_gemma":[0.9975322,0.001342292,0.0001843348,0.0004308514,0.0003192827,0.0001910346],"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":[0.0006083602,0.00006568391,0.000590589,0.0001625666,0.0000565113,0.00009932561,0.00003541297,0.003100281,0.9478514,0.004193312,0.001040132,0.04219648],"study_design_scores_gemma":[0.00005703339,0.000392203,0.007673317,0.00004044705,0.0001353335,0.001058104,0.00003567262,0.1018231,0.8752719,0.008377851,0.005076389,0.00005867963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4659566,0.002318043,0.5004228,0.001232177,0.0003428998,0.00007336464,0.0004348198,0.0028121,0.0264072],"genre_scores_gemma":[0.9156601,0.0007377249,0.07523254,0.0008845657,0.0001352311,0.00009201015,0.0005733402,0.0008784742,0.005805947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005856934,"threshold_uncertainty_score":0.01959336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009154829544359198,"score_gpt":0.2549482382341783,"score_spread":0.2457934086898191,"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."}}