{"id":"W2974512905","doi":"10.3389/fpsyg.2019.02161","title":"Age Differences, Age Changes, and Generalizability in Marathon Running by Master Athletes","year":2019,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Generalizability theory; Quartile; Cohort; Demography; Athletes; Psychology; Cohort effect; Gerontology; Statistics; Medicine; Developmental psychology; Mathematics; Physical therapy; Confidence interval","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":[0.009098621,0.0002675384,0.0003488817,0.002011067,0.000372713,0.0009665019,0.0005745084,0.0005124071,0.001845834],"category_scores_gemma":[0.03596353,0.0002436801,0.0007017596,0.00143839,0.0007502889,0.001517824,0.001084759,0.0006140299,0.0002776919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004026069,"about_ca_system_score_gemma":0.0003494103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01140939,"about_ca_topic_score_gemma":0.01189258,"domain_scores_codex":[0.9967517,0.001211977,0.0002512274,0.0009966735,0.0005247768,0.0002637782],"domain_scores_gemma":[0.9782965,0.009111041,0.007054025,0.003553313,0.001298233,0.0006868856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004932566,0.00001611571,0.9948041,0.00001006606,0.00009995797,0.00002561325,0.0008527868,0.0001976972,0.00008000437,0.0001071392,0.00006285625,0.003694404],"study_design_scores_gemma":[8.864349e-7,0.00005620173,0.9988801,0.000005990496,0.00001264562,0.00003788555,0.0005185201,0.0002063627,0.00002820035,0.0001200113,0.0001299942,0.00000322265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974617,0.0004798287,0.0006058417,0.0001186568,0.00001446185,0.00001294652,0.0002198841,0.0000126074,0.001074095],"genre_scores_gemma":[0.9991786,0.0001347959,0.0001190481,0.00002392073,0.00001667923,0.000006476216,0.0002869803,0.000006704696,0.000226798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01140939,"threshold_uncertainty_score":0.04811865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03433013483890197,"score_gpt":0.2397961210160378,"score_spread":0.2054659861771358,"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."}}