{"id":"W2085019030","doi":"10.1080/14639220512331311562","title":"The effect of variability in temporal information on the control of a dynamic task","year":2005,"lang":"en","type":"article","venue":"Theoretical Issues in Ergonomics Science","topic":"Sport Psychology and Performance","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale","keywords":"Task (project management); Control (management); Computer science; Temporal difference learning; Uncertainty analysis; Temporal database; Sensitivity analysis; Artificial intelligence; Data mining; Simulation; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003495324,0.0004767524,0.0004254843,0.0005278224,0.0002962612,0.001105132,0.0004374136,0.0005837276,0.001165604],"category_scores_gemma":[0.05746471,0.000363017,0.000331884,0.0002510987,0.0006891697,0.0008864901,0.001016516,0.0007270638,0.0000874191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003539169,"about_ca_system_score_gemma":0.0003055784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007720819,"about_ca_topic_score_gemma":0.0005854975,"domain_scores_codex":[0.9964443,0.001501687,0.0003453543,0.0004757166,0.000989735,0.0002433416],"domain_scores_gemma":[0.8861373,0.0989062,0.008128783,0.003795469,0.001275654,0.001756605],"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":[0.02446514,0.002906165,0.2785273,0.001068354,0.001086713,0.001291854,0.00723143,0.06268761,0.3721534,0.00423165,0.0004080674,0.2439423],"study_design_scores_gemma":[0.0004421344,0.01582901,0.8121111,0.000188411,0.0005821576,0.001416982,0.002328244,0.0887576,0.06613296,0.009907619,0.001983386,0.0003205137],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934605,0.000125093,0.005392094,0.00003221174,0.000005658022,0.00001685117,0.00001633642,0.00001634933,0.0009347767],"genre_scores_gemma":[0.998238,0.00003787373,0.00158725,0.00001418543,0.000006804232,0.00001492832,0.00001992536,0.000005132999,0.00007588936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003495324,"threshold_uncertainty_score":0.01848525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003897001874498737,"score_gpt":0.30099080487154,"score_spread":0.2970938029970412,"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."}}