{"id":"W2641082816","doi":"","title":"What's your next move? Directional biases for sequential limb and eye movements","year":2010,"lang":"en","type":"article","venue":"Journal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Eye movement; Offset (computer science); Movement (music); Computer science; Fixation (population genetics); Computer vision; Artificial intelligence; Saccade; Communication; Physical medicine and rehabilitation; Neuroscience; Psychology; Biology; Physics; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009794459,0.0001987809,0.0002438577,0.0002719331,0.0001076706,0.0005415425,0.0001567372,0.0002875054,0.001833266],"category_scores_gemma":[0.01349315,0.0001738292,0.0002066836,0.0001641119,0.0001972401,0.0004399691,0.0002378066,0.0004207042,0.0003332108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001781675,"about_ca_system_score_gemma":0.0001880936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001228239,"about_ca_topic_score_gemma":0.002027242,"domain_scores_codex":[0.9995778,0.0001075544,0.00003309313,0.0001096461,0.0001341182,0.00003763819],"domain_scores_gemma":[0.9960169,0.002449222,0.0008018051,0.0002966331,0.0003125687,0.0001227458],"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":[0.002756867,0.0001281259,0.09366307,0.000516728,0.0001623686,0.0002559181,0.001366394,0.0029121,0.7542472,0.002247508,0.001024352,0.1407194],"study_design_scores_gemma":[0.0001222963,0.0007846447,0.9005286,0.0001005796,0.0001699859,0.0007395386,0.0005494181,0.01773463,0.0711625,0.004932046,0.00309475,0.00008104326],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863757,0.0003154548,0.007272145,0.0001844112,0.00004062867,0.00003133827,0.0001587496,0.0001383181,0.005483153],"genre_scores_gemma":[0.9953777,0.0001170222,0.00359936,0.00007180985,0.000007842305,0.0000151946,0.00006454169,0.00005658567,0.0006899633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001833266,"threshold_uncertainty_score":0.006132841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03469565294439468,"score_gpt":0.2858348975365325,"score_spread":0.2511392445921378,"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."}}