{"id":"W1968563762","doi":"10.1371/journal.pcbi.1002253","title":"Learning the Optimal Control of Coordinated Eye and Head Movements","year":2011,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Vestibular and auditory disorders","field":"Neuroscience","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University; Bundesministerium für Bildung und Forschung; City University of New York","keywords":"Eye movement; Computer science; Gaze; Head (geology); Adaptation (eye); Mechanism (biology); Artificial intelligence; Neuroscience; Psychology; Physics; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000477217,0.0002759402,0.0003039583,0.0001692787,0.0001856951,0.0005252235,0.0005478024,0.000457698,0.0008595982],"category_scores_gemma":[0.0018208,0.0001936359,0.0002432765,0.0001239357,0.0006694063,0.0006224639,0.0005828983,0.0004580714,0.00009369004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004309291,"about_ca_system_score_gemma":0.0006525278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001859691,"about_ca_topic_score_gemma":0.001972278,"domain_scores_codex":[0.9998659,0.00002808682,0.000007645176,0.00004378633,0.00002579014,0.00002881443],"domain_scores_gemma":[0.9997033,0.0001363059,0.00005958011,0.00003478805,0.00004272039,0.0000232523],"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":[0.00008322147,0.00007069876,0.0014039,0.00005864941,0.00005118005,0.00008452388,0.0001247621,0.8768683,0.02475981,0.04051689,0.0005176762,0.05546043],"study_design_scores_gemma":[0.00001621702,0.00003503147,0.0004693273,0.000002335399,0.000007343807,0.00001253537,0.000008989587,0.9881143,0.00155014,0.009609857,0.0001669407,0.000006917941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1754853,0.0001131593,0.8197163,0.0002292628,0.00002298077,0.00003205557,0.00001630753,0.0002511996,0.004133443],"genre_scores_gemma":[0.9766412,0.00004602375,0.02252224,0.0000251067,0.000008743243,0.00003882802,0.000008054752,0.00001524555,0.0006945781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001859691,"threshold_uncertainty_score":0.003697693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03541443993231216,"score_gpt":0.266754083468749,"score_spread":0.2313396435364369,"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."}}