{"id":"W1185765131","doi":"","title":"Luminance Spatial Scale and Local Stereopsis","year":2002,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Stereopsis; Luminance; Scale (ratio); Artificial intelligence; Computer science; Computer vision; Optometry; Geography; Cartography; Medicine","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":[0.0001951545,0.0001386326,0.0002198246,0.0004789866,0.0002329921,0.0007868221,0.0003054302,0.0003189605,0.003892156],"category_scores_gemma":[0.00155321,0.0001369571,0.0002139377,0.0002647977,0.0005710312,0.0009745511,0.0006003896,0.0003584252,0.0002858895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003145909,"about_ca_system_score_gemma":0.0002951675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001036049,"about_ca_topic_score_gemma":0.001006638,"domain_scores_codex":[0.9999024,0.00001159828,0.000004451167,0.00001877148,0.00004082352,0.00002211425],"domain_scores_gemma":[0.9995267,0.0001911962,0.0001025295,0.0000565535,0.00006369114,0.00005925931],"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":[0.002437789,0.0001962265,0.009925596,0.0002220812,0.00005255494,0.0009121482,0.0005764629,0.003303028,0.7575842,0.1211561,0.001593477,0.1020403],"study_design_scores_gemma":[0.0004402739,0.001108564,0.5677058,0.00008531177,0.000152716,0.003431171,0.0008945137,0.0335862,0.1376364,0.2480281,0.006825247,0.000105705],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486393,0.001519975,0.0126,0.0004542557,0.00006059426,0.00001901412,0.0001036521,0.0001163166,0.03648682],"genre_scores_gemma":[0.9967442,0.0002699421,0.001222429,0.00005699884,0.00002392053,0.000006229495,0.00003367126,0.00002153416,0.001621183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003892156,"threshold_uncertainty_score":0.01302058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08080087053017473,"score_gpt":0.3421214616480485,"score_spread":0.2613205911178738,"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."}}