{"id":"W2095172062","doi":"10.1109/cjece.2009.5291203","title":"Neurofuzzy prediction for gaze control","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Vestibular and auditory disorders","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Gaze; Artificial intelligence; Adaptive neuro fuzzy inference system; Task (project management); Process (computing); Computer vision; Fuzzy control system; Control (management); Object (grammar); Inference; Fuzzy logic; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000472459,0.00006556504,0.0001040396,0.0001341463,0.00005695108,0.00004468889,0.00008203799,0.00002784765,0.000001665275],"category_scores_gemma":[0.0001748751,0.0000600461,0.00004347431,0.000109227,0.00000907617,0.00008331957,0.000001114961,0.0001271946,4.073332e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002092219,"about_ca_system_score_gemma":0.00007825653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004717516,"about_ca_topic_score_gemma":0.000003071847,"domain_scores_codex":[0.9995208,0.00001016924,0.0001329022,0.00008273821,0.00005652551,0.0001968119],"domain_scores_gemma":[0.9995081,0.0001101252,0.00003336703,0.00003389066,0.00002560155,0.0002889448],"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":[0.0001371051,0.0001126045,0.002873087,0.00005657186,0.00005825238,0.0006198152,0.0003872329,0.5409949,0.09335334,0.03748269,0.01712795,0.3067964],"study_design_scores_gemma":[0.00126275,0.001771603,0.01216544,0.00005309233,0.00002925463,0.0006654747,0.000001076409,0.9562631,0.002814835,0.001783394,0.02298263,0.000207358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08079423,0.000346438,0.9173584,0.0006450089,0.000711662,0.00009240362,0.000006644397,0.0000164142,0.00002881363],"genre_scores_gemma":[0.9979954,0.00001019581,0.000757652,0.0007208384,0.0005034016,6.167904e-7,1.575189e-7,0.000005185839,0.000006530201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9172012,"threshold_uncertainty_score":0.2448609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006196963278532154,"score_gpt":0.1747887956306497,"score_spread":0.1685918323521175,"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."}}