{"id":"W2119698875","doi":"10.1109/tnn.2008.2000447","title":"A Neural Model for Compensation of Sensory Abnormalities in Autism Through Feedback From a Measure of Global Perception","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Autism; Sensory system; Measure (data warehouse); Perception; Compensation (psychology); Computer science; Neurophysiology; Artificial neural network; Artificial intelligence; Cognitive psychology; Speech recognition; Neuroscience; Psychology; Data mining; Developmental psychology","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":[0.0001019997,0.0002288091,0.000369361,0.00008881867,0.0002031217,0.0000146978,0.0002573293,0.0001729781,0.00004406011],"category_scores_gemma":[0.00001355254,0.0002368091,0.000209891,0.0004953559,0.0003496167,0.0004341464,0.000003915311,0.0004051893,0.000002937178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001339046,"about_ca_system_score_gemma":0.0000677864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008001755,"about_ca_topic_score_gemma":0.0006591404,"domain_scores_codex":[0.9979005,0.0002469057,0.0005278501,0.0004498101,0.0004409899,0.0004339109],"domain_scores_gemma":[0.9991286,0.0003058101,0.0001577038,0.0003117913,0.00003244894,0.00006359575],"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":[0.0007187371,0.0002696151,0.0002945439,0.0000247602,0.000009157769,0.000006419802,0.001419185,0.9792657,0.01521789,0.0008273176,0.00002012992,0.001926559],"study_design_scores_gemma":[0.001316144,0.0002124126,0.007190385,0.00003702499,0.00001822467,0.00002788396,0.00009730287,0.9825491,0.006093016,0.002276161,0.000001058591,0.0001812268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6350813,0.00003223948,0.3633299,0.00052924,0.0001910012,0.0004975781,0.0002168126,0.00004818032,0.00007374796],"genre_scores_gemma":[0.9989306,0.0001246014,0.0005841262,0.0001670646,0.00002511912,0.00006401884,0.000006513884,0.00002738034,0.0000705639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3638493,"threshold_uncertainty_score":0.9656795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07792584610969892,"score_gpt":0.3006184927202792,"score_spread":0.2226926466105802,"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."}}