{"id":"W2944935962","doi":"10.12922/jshp.v7i1.140","title":"Learning How to Prepare Athletes for Peak Performance: Use of Mental Imagery Training as a Psychological Strategy to Enhancing Motor Learning, Retention and Transfer of Sport Rifle Marksmanship","year":2019,"lang":"en","type":"article","venue":"Journal of Sport and Human Performance","topic":"Sport Psychology and Performance","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Laurentian University","funders":"","keywords":"Kinesthetic learning; Athletes; Mental image; Motor imagery; Psychology; Motor learning; Modality (human–computer interaction); Motor skill; Training (meteorology); Rifle; Physical medicine and rehabilitation; Applied psychology; Cognitive psychology; Cognition; Physical therapy; Developmental psychology; Computer science; Artificial intelligence; Engineering; Brain–computer interface; Medicine; Electroencephalography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001373589,0.0003029863,0.0007845115,0.0004328423,0.0002023111,0.00004443511,0.0002151879,0.00023861,0.0004011129],"category_scores_gemma":[0.0000099881,0.0002687963,0.0001840135,0.0001909225,0.0001477287,0.0007011278,0.00003312149,0.0006036591,0.000006308754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002699764,"about_ca_system_score_gemma":0.00003749879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009087556,"about_ca_topic_score_gemma":0.000008051893,"domain_scores_codex":[0.9977787,0.00001310989,0.0009787438,0.0004445983,0.0003158171,0.0004690462],"domain_scores_gemma":[0.9987245,0.00002647744,0.0005661319,0.0002291478,0.0002394296,0.0002143092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00439264,0.0001651649,0.9579279,0.0003575895,0.0001213045,0.00001306409,0.01066425,0.0002002913,0.01528067,0.0001799879,0.0002372035,0.01045992],"study_design_scores_gemma":[0.001819922,0.01224489,0.9713082,0.0006302446,0.00008271464,0.0003078025,0.003048484,0.0001168871,0.001528733,0.000009441249,0.008582947,0.000319718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976571,0.0002009185,0.00002156621,0.00005170426,0.0004449968,0.0006278096,0.000005238327,0.00002683205,0.0009638299],"genre_scores_gemma":[0.9948322,0.0002597042,0.0004281978,0.00008699545,0.0002121074,0.00002593476,0.00002015539,0.00004517304,0.004089541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01375193,"threshold_uncertainty_score":0.9999764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05071152259595881,"score_gpt":0.3222614906935255,"score_spread":0.2715499680975667,"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."}}