{"id":"W2023841961","doi":"10.1080/00207450500505373","title":"VISUALIZATION IN THE NEUROSCIENCES: SEEING ABSTRACTIONS IN REAL TIME","year":2006,"lang":"en","type":"review","venue":"International Journal of Neuroscience","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"New York Institute of Technology","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Feature (linguistics); Data visualization; Element (criminal law); Information visualization; Data science; Artificial intelligence; Information retrieval","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":[0.001689719,0.001416905,0.001590338,0.004909849,0.0006481428,0.003342257,0.001921879,0.003306997,0.005592215],"category_scores_gemma":[0.002367225,0.0005325921,0.0006499472,0.004766311,0.003983852,0.008980649,0.001526071,0.003200607,0.005010122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001286231,"about_ca_system_score_gemma":0.001281835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001540637,"about_ca_topic_score_gemma":0.001519409,"domain_scores_codex":[0.9993436,0.0001896185,0.00005698536,0.00009478174,0.0002733586,0.00004161257],"domain_scores_gemma":[0.9983796,0.0009893496,0.00009003071,0.0001159046,0.0003220605,0.0001031441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003711779,0.00005526111,0.0001554997,0.007534935,0.00005615523,0.000179058,0.0006460325,0.0006249075,0.001711001,0.05424145,0.06141861,0.87334],"study_design_scores_gemma":[0.00001121934,0.00003760117,0.0004444422,0.002293804,0.00002264845,0.001255723,0.000230636,0.0002663284,0.0005655853,0.02979211,0.9650471,0.00003282852],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001796568,0.9818859,0.006710841,0.001689238,0.0009473749,0.00001631016,0.00002063998,0.0001388206,0.008411278],"genre_scores_gemma":[0.002231879,0.9865501,0.005704172,0.0007734596,0.001021521,0.00003832194,0.00003609374,0.00003389872,0.003610507],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005592215,"threshold_uncertainty_score":0.01870787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0932384028739299,"score_gpt":0.3976314214114072,"score_spread":0.3043930185374774,"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."}}