{"id":"W2381003833","doi":"10.1038/srep25692","title":"Orientation tuning of binocular summation: a comparison of colour to achromatic contrast","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Achromatic lens; Contrast (vision); Orientation (vector space); Binocular vision; Computer science; Optics; Artificial intelligence; Computer vision; Physics; Mathematics; Geometry","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":[0.0003656907,0.0001975861,0.0002138235,0.0005974463,0.0001309013,0.0002840466,0.0001964314,0.0001335813,0.0006805891],"category_scores_gemma":[0.00163154,0.0001860951,0.0002205315,0.0002621963,0.0002572903,0.0002947252,0.0003943946,0.000205838,0.00008864284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002752531,"about_ca_system_score_gemma":0.0001265022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001435383,"about_ca_topic_score_gemma":0.001464172,"domain_scores_codex":[0.9998116,0.00003770527,0.000006950259,0.00003666708,0.00007183127,0.00003529959],"domain_scores_gemma":[0.9994387,0.0002703115,0.00009283252,0.00005864525,0.00008183734,0.00005769893],"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":[0.0004712268,0.00005107404,0.02004274,0.00005725719,0.00003779575,0.00004424611,0.0001005393,0.001906505,0.9608422,0.0005492485,0.00005593222,0.01584114],"study_design_scores_gemma":[0.00003638988,0.0003977959,0.696914,0.00001789304,0.00007439041,0.0006673034,0.00008640408,0.04949239,0.2497499,0.002039798,0.0004828467,0.00004095101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817555,0.0002523467,0.01644272,0.00001495057,0.000005388409,0.00001087766,0.00005550595,0.00004764222,0.001415061],"genre_scores_gemma":[0.998486,0.00006052133,0.001313442,0.000009144319,0.000002710079,0.000004040375,0.00004319501,0.000009171603,0.00007175627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001435383,"threshold_uncertainty_score":0.002854109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0686145618764301,"score_gpt":0.3567427149321166,"score_spread":0.2881281530556865,"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."}}