{"id":"W2163627919","doi":"10.1093/cercor/bhn177","title":"Decoding the Cortical Transformations for Visually Guided Reaching in 3D Space","year":2008,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; York University","funders":"","keywords":"Microstimulation; Computer science; Transformation (genetics); Neurophysiology; Neural decoding; Receptive field; Reference frame; Population; Artificial neural network; Artificial intelligence; Decoding methods; Frame (networking); Computer vision; Pattern recognition (psychology); Neuroscience; Algorithm; Psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001941932,0.00009239512,0.0001148291,0.00005527446,0.0004231826,0.00003624823,0.000158518,0.00003797941,0.00002889808],"category_scores_gemma":[0.0005538081,0.00006747718,0.00006611084,0.0001595506,0.00006342902,0.0002676994,0.00001272955,0.0001592085,0.0000190445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003753062,"about_ca_system_score_gemma":0.00005085027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002838063,"about_ca_topic_score_gemma":0.00007183518,"domain_scores_codex":[0.9990489,0.00008754333,0.0002646397,0.0001931413,0.0001621038,0.0002436708],"domain_scores_gemma":[0.9993559,0.0003846358,0.00005583306,0.0001287178,0.00002352843,0.00005137276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000254793,0.0002395883,0.006073871,0.00005143309,0.00001151629,0.0000407713,0.01023814,0.001136504,0.8234074,0.1391255,0.001260183,0.01816027],"study_design_scores_gemma":[0.003906768,0.0002719656,0.2671366,0.00005769655,0.0000358537,0.0001919435,0.000388508,0.701726,0.01308933,0.003243653,0.009441613,0.0005100786],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9436654,0.00001548999,0.05080679,0.001499198,0.000171617,0.0005677501,0.000008668718,0.0000614392,0.00320369],"genre_scores_gemma":[0.9979568,0.00001527923,0.0007404598,0.0008359276,0.000067913,0.00005352495,0.000003926913,0.00001088087,0.0003152809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8103181,"threshold_uncertainty_score":0.3254821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07386024466557208,"score_gpt":0.3035126605947336,"score_spread":0.2296524159291615,"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."}}