{"id":"W3107191008","doi":"10.1371/journal.pcbi.1008457","title":"Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain","year":2020,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Mental Health; Canadian Institute for Advanced Research; Princeton University; National Institutes of Health; National Science Foundation","keywords":"Computer science; Voxel; Functional magnetic resonance imaging; Artificial intelligence; Neural coding; Modularity (biology); Pattern recognition (psychology); Neuroscience; Psychology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004904021,0.0002562704,0.0002741918,0.000773787,0.0002435417,0.0007426441,0.0002446759,0.0004112377,0.001248199],"category_scores_gemma":[0.002380671,0.0001933402,0.000369154,0.0005056277,0.001021363,0.001369421,0.0006733775,0.0003932009,0.0001853925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001867943,"about_ca_system_score_gemma":0.0002953494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009783501,"about_ca_topic_score_gemma":0.002313707,"domain_scores_codex":[0.9998838,0.00003031807,0.000005068398,0.00004430686,0.00002050007,0.00001600596],"domain_scores_gemma":[0.9995846,0.0002306637,0.00006111124,0.00006520058,0.00002483755,0.00003355323],"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":[0.0009269352,0.0001046245,0.03202305,0.000355053,0.0002575722,0.0004498699,0.002498536,0.03287726,0.5767608,0.03309388,0.001919277,0.3187331],"study_design_scores_gemma":[0.00007713243,0.0004519283,0.305727,0.00006506672,0.0001579455,0.002375263,0.001187477,0.3343486,0.07697623,0.2762986,0.002208182,0.0001264884],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8080399,0.0003170937,0.1888969,0.0004349764,0.000009247798,0.00001215893,0.0001731001,0.0002250878,0.001891576],"genre_scores_gemma":[0.9837099,0.0001017952,0.01569631,0.00004149296,0.00001027689,0.000008666256,0.00008688231,0.00003976162,0.000304768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001248199,"threshold_uncertainty_score":0.004175663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1373042480538121,"score_gpt":0.3531253634849201,"score_spread":0.215821115431108,"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."}}