{"id":"W2060416571","doi":"10.1533/abbi.2005.0024","title":"Design, Sensing and Control of a Robotic Prosthetic Eye for Natural Eye Movement","year":2006,"lang":"en","type":"article","venue":"Applied Bionics and Biomechanics","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Alberta; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Eye movement; Artificial intelligence; Computer vision; Computer science; SIGNAL (programming language); Artificial neural network; Sensor fusion; Frame (networking); Eye tracking; Engineering","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":[0.0001984244,0.0001595416,0.0002132952,0.00007879328,0.0001241664,0.00007668509,0.00009131537,0.00007124734,7.05918e-7],"category_scores_gemma":[0.00001169907,0.0001240578,0.00003542802,0.0001367407,0.00007400973,0.00003249676,0.00006579854,0.00006749322,7.54929e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001411446,"about_ca_system_score_gemma":0.00001739106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009139458,"about_ca_topic_score_gemma":0.000002592556,"domain_scores_codex":[0.9989951,0.00002205743,0.0002429075,0.0003571305,0.0001358564,0.0002469396],"domain_scores_gemma":[0.9995465,0.0001252025,0.0001275561,0.0001246756,0.00003672895,0.00003928436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006098749,0.00004515213,0.000002192269,0.00005026281,0.000006199349,0.000001226017,0.00004118545,0.00004641736,0.9750171,0.01408793,0.00002214434,0.01061919],"study_design_scores_gemma":[0.0008581472,0.000193843,0.000007684847,0.000021648,0.00002074758,0.000004516005,0.00002411806,0.2256426,0.7580311,0.01479671,0.0002551859,0.0001436749],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4206356,0.0005679679,0.5761532,0.0007775042,0.0002904961,0.001449782,0.00002782987,0.00006098271,0.00003666255],"genre_scores_gemma":[0.9932926,0.0000338066,0.005991996,0.0005631241,0.00003248848,0.00001050331,0.00000306557,0.00001436565,0.00005808266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.572657,"threshold_uncertainty_score":0.5058929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01405506293155628,"score_gpt":0.2332199852835704,"score_spread":0.2191649223520141,"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."}}