{"id":"W2697441045","doi":"10.1249/fit.0000000000000067","title":"HIGH-INTENSITY INTERVAL TRAINING","year":2014,"lang":"en","type":"article","venue":"ACSMʼs Health & Fitness Journal","topic":"Cardiovascular and exercise physiology","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus","funders":"","keywords":"High-intensity interval training; Interval training; Intensity (physics); Continuous training; Interval (graph theory); Training (meteorology); Boosting (machine learning); Psychology; Physical therapy; Aerobic exercise; Medicine; Physical medicine and rehabilitation; Computer science; Artificial intelligence; Mathematics; Physics","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":[0.0004819756,0.0003275434,0.000284769,0.0003108997,0.0003505477,0.0003529283,0.00085671,0.0006550134,0.03066637],"category_scores_gemma":[0.0007941933,0.00008652242,0.0003448284,0.000132316,0.0001146173,0.0003279355,0.0006275738,0.0008443824,0.00377589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002375037,"about_ca_system_score_gemma":0.000639273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007219951,"about_ca_topic_score_gemma":0.001197324,"domain_scores_codex":[0.9997862,0.00002603289,0.00001113416,0.00003660479,0.00009371211,0.00004636887],"domain_scores_gemma":[0.9996921,0.00006099838,0.00002760989,0.0000168313,0.0000758067,0.0001266473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002399555,0.01509862,0.006238216,0.001665732,0.00006756804,0.0001595461,0.0001925547,0.001271039,0.008945454,0.001376101,0.02114243,0.9414433],"study_design_scores_gemma":[0.01085691,0.1127277,0.4402574,0.01185879,0.0005627327,0.005561457,0.00146759,0.02012248,0.03474344,0.01547149,0.3460627,0.0003072504],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6268223,0.01343601,0.08015236,0.006973827,0.006019976,0.007716944,0.001993279,0.002046141,0.2548391],"genre_scores_gemma":[0.8002909,0.009473176,0.07019411,0.004116514,0.002053374,0.00429154,0.00193765,0.0001421988,0.1075005],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03066637,"threshold_uncertainty_score":0.1025892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.036356683927255,"score_gpt":0.3112735698986603,"score_spread":0.2749168859714053,"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."}}