{"id":"W4290706255","doi":"10.1016/j.neuroscience.2022.07.026","title":"A Guide for the Multiplexed: The Development of Visual Feature Maps in the Brain","year":2022,"lang":"en","type":"review","venue":"Neuroscience","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"ENCODE; Computer science; Feature (linguistics); Neuroscience; Focus (optics); Feature extraction; Encoding (memory); Artificial intelligence; Multiplexing; Biological neural network; Pattern recognition (psychology); Machine learning; Biology","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":[0.001088072,0.002053717,0.001276884,0.003799795,0.0006082553,0.001592133,0.002054676,0.003105602,0.007832113],"category_scores_gemma":[0.001450811,0.0006324589,0.0007405074,0.002651847,0.002858276,0.00472441,0.001577826,0.007629108,0.01207164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001545552,"about_ca_system_score_gemma":0.00208019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002710349,"about_ca_topic_score_gemma":0.003765745,"domain_scores_codex":[0.9996114,0.00007882383,0.00005874646,0.0000862819,0.0001365804,0.00002812304],"domain_scores_gemma":[0.9992329,0.0003611045,0.00006546638,0.00005103888,0.000188256,0.0001013129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005850732,0.00005978829,0.0001440772,0.005453883,0.0000554119,0.0003483598,0.0002668295,0.0005114771,0.00212837,0.06082604,0.4530959,0.4770514],"study_design_scores_gemma":[0.000003818426,0.00001284391,0.000113734,0.0006531482,0.000006605291,0.0004163194,0.00001644765,0.00003463081,0.0001170185,0.006699789,0.9919166,0.000009050915],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009459934,0.9751834,0.005085335,0.005220506,0.004388187,0.00002766919,0.0001952697,0.0001384315,0.009666614],"genre_scores_gemma":[0.001059071,0.9709187,0.006438007,0.004871209,0.00232271,0.00007913002,0.0003237667,0.00008149065,0.01390589],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007832113,"threshold_uncertainty_score":0.02620101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1155803961740359,"score_gpt":0.372601619921031,"score_spread":0.257021223746995,"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."}}