{"id":"W2901031299","doi":"10.1167/18.12.6","title":"Magnetoencephalography adaptation reveals depth-cue-invariant object representations in the visual cortex","year":2018,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"McGill University Health Centre","keywords":"Magnetoencephalography; Visual cortex; Invariant (physics); Adaptation (eye); Psychology; Computer science; Computer vision; Artificial intelligence; Neuroscience; Communication; Cognitive psychology; Mathematics; Electroencephalography","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":[0.00008265906,0.0001440572,0.0001309792,0.000146316,0.0000520001,0.0001347243,0.00007476869,0.0001248283,0.0006849043],"category_scores_gemma":[0.00040345,0.00009770888,0.0001060815,0.00008969088,0.0001937838,0.0001123034,0.000141199,0.0002430235,0.00008168608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001118635,"about_ca_system_score_gemma":0.00007216083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008532534,"about_ca_topic_score_gemma":0.001519136,"domain_scores_codex":[0.9999679,0.000005175674,0.00000149821,0.000009352631,0.000007699423,0.000008244259],"domain_scores_gemma":[0.9999299,0.00002319913,0.00001830308,0.00000944928,0.000008068751,0.00001098924],"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":[0.0001144092,0.000007268418,0.001168523,0.00001172331,0.000006516574,0.00006365281,0.00002658048,0.00006831763,0.9954275,0.00002841018,0.00003047921,0.003046658],"study_design_scores_gemma":[0.00003623553,0.0003378347,0.8459304,0.000005242854,0.00002797275,0.001004889,0.0000820632,0.002525843,0.1493129,0.0003074564,0.0004166031,0.00001255818],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973978,0.0000854819,0.00202255,0.00002505424,0.000004148992,0.000007873194,0.00005578388,0.0000278444,0.0003734403],"genre_scores_gemma":[0.9985722,0.00009162686,0.0009492447,0.00002704791,0.000005300739,0.000008086879,0.00006733737,0.000007814814,0.0002711945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008532534,"threshold_uncertainty_score":0.002291262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0547722147879464,"score_gpt":0.3657290636201308,"score_spread":0.3109568488321844,"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."}}