{"id":"W2485949287","doi":"10.1152/jn.00605.2015","title":"Modeling eye-head gaze shifts in multiple contexts without motor planning","year":2016,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Canadian Institutes of Health Research","keywords":"Gaze; Motor planning; Head (geology); Psychology; Eye movement; Cognitive psychology; Communication; Computer science; Neuroscience; Computer vision; Geology","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":[0.00011066,0.0001443387,0.000377299,0.0003109888,0.00004995259,0.00001848221,0.0007971419,0.00009817322,0.000002548111],"category_scores_gemma":[0.0003243063,0.00009350135,0.0000919226,0.0001593142,0.00008401043,0.0002848727,0.0001502738,0.000348017,0.0000187984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003785285,"about_ca_system_score_gemma":0.00005391863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007301187,"about_ca_topic_score_gemma":0.000002179077,"domain_scores_codex":[0.9986532,0.0001545616,0.0004663297,0.0002620396,0.000139102,0.0003247329],"domain_scores_gemma":[0.9990625,0.0002207188,0.0002396675,0.0002788032,0.0001250875,0.00007316573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000158976,0.0001143895,0.008618277,0.000007175517,0.00001915183,0.0004686865,0.0001396587,0.006998219,0.9623217,0.0009666718,0.00001824563,0.02016886],"study_design_scores_gemma":[0.004711236,0.002457117,0.7075232,0.0005876528,0.00001320588,0.0002589122,0.00002967878,0.2694853,0.002854648,0.01103455,0.0005675919,0.0004769173],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8688207,0.0000533462,0.1295357,0.001023078,0.0004524287,0.00004343968,8.625759e-7,0.00004689646,0.0000235439],"genre_scores_gemma":[0.9946061,0.00002205488,0.004997707,0.0002218128,0.0001116403,0.000001949984,6.900282e-8,0.00001167723,0.00002698748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9594671,"threshold_uncertainty_score":0.3812875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04105814361992605,"score_gpt":0.2921540970556028,"score_spread":0.2510959534356768,"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."}}