{"id":"W4214939687","doi":"10.1080/17461391.2022.2048894","title":"Implementation of multiple statistical methods to estimate variability and individual response to training","year":2022,"lang":"en","type":"article","venue":"European Journal of Sport Science","topic":"Sports Performance and Training","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Australian Research Council","keywords":"Repeated measures design; High-intensity interval training; Medicine; Physical therapy; Interval training; Reliability (semiconductor); Confidence interval; Time point; Physical medicine and rehabilitation; Analysis of variance; Statistics; Mathematics; Internal 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3214343,0.002570714,0.003031044,0.004206114,0.001542439,0.004455889,0.005304176,0.002889349,0.004318024],"category_scores_gemma":[0.519425,0.001690635,0.005869096,0.003953807,0.004915702,0.003955593,0.004197158,0.007260743,0.0008402042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002216889,"about_ca_system_score_gemma":0.005291677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003431156,"about_ca_topic_score_gemma":0.002826243,"domain_scores_codex":[0.4670453,0.4710958,0.01453819,0.01184996,0.03398117,0.001489566],"domain_scores_gemma":[0.351602,0.5158709,0.02755201,0.0674509,0.03609816,0.001425905],"domain_codex":"methods","domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002528518,0.001139342,0.09060805,0.00409059,0.01538193,0.0005006762,0.004494966,0.03679549,0.008868387,0.05945021,0.01767521,0.7584667],"study_design_scores_gemma":[0.001218128,0.00740238,0.1078414,0.003613015,0.004216114,0.0009241942,0.001616054,0.6655139,0.02325756,0.1302688,0.05307423,0.001054354],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006543668,0.000270454,0.9889417,0.000726253,0.0004241381,0.00119002,0.0001708811,0.000970051,0.0007629227],"genre_scores_gemma":[0.1163088,0.0002093586,0.8761133,0.0005624235,0.0002434465,0.005344281,0.0001746953,0.000553909,0.0004897199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3214343,"threshold_uncertainty_score":0.8367923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.075711523360129,"score_gpt":0.4286030712838969,"score_spread":0.3528915479237679,"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."}}