{"id":"W2036319355","doi":"10.1016/j.neucom.2006.10.058","title":"Toward direct links between model networks and experimental data","year":2006,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Rehabilitation Institute; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001135743,0.0001454561,0.0001477843,0.00004220754,0.0002276088,0.0001212545,0.0003069959,0.00007837221,0.000001920406],"category_scores_gemma":[0.00004355391,0.0001392275,0.00002569581,0.0001365174,0.00005050691,0.0001954447,0.0005780573,0.00030898,0.000003506011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001198664,"about_ca_system_score_gemma":0.000008305422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002478849,"about_ca_topic_score_gemma":0.000001019315,"domain_scores_codex":[0.9986426,0.00006143405,0.0002047482,0.0006506318,0.0001627006,0.0002778435],"domain_scores_gemma":[0.9993241,0.0002270834,0.00007879563,0.0003051538,0.000007961204,0.00005689764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003469826,0.0001460035,0.007857275,0.00002955926,0.000005359841,0.00008103027,0.00009062781,0.569641,0.3880359,0.001460068,0.002388269,0.03023024],"study_design_scores_gemma":[0.0001964618,0.0000376661,0.001710587,0.00000850153,0.000005614827,0.00001624134,0.000002537411,0.9839942,0.01330598,0.0001245227,0.0004583653,0.0001393333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982757,0.00005073574,0.01336191,0.0002280838,0.0002689277,0.0001698849,0.00001546631,0.0001916903,0.00295635],"genre_scores_gemma":[0.99823,0.0000044608,0.0004207706,0.0006834913,0.0005195516,0.000001869077,0.00001732599,0.00002466712,0.00009784311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4143532,"threshold_uncertainty_score":0.5677533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07895029052850933,"score_gpt":0.2858009495147158,"score_spread":0.2068506589862065,"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."}}