Resistance Training Guidelines American Heart Association (AHA), American College of Sports Medicine (ACSM), and Canadian Association of Cardiac Rehabilitation (CACR) Guidelines for Resistance Training
Bibliographic record
Abstract
and rehabilitation for either the ACSM or the AHA. In 1990, ACSM first recognized resistance/strength training as an integral element of a well-rounded program for healthy adults. Most recently, in February 2000, a Scientific Advisory was released by the AHA on resistance training in healthy adults and in individuals with cardiovascular disease (CVD), recognizing the beneficial relationship to health. Concurrently, the ACSM released the 6th edition of the Guidelines for Exercise Testing and Training and the CACR released the first edition of the Canadian Guidelines for Cardiac Rehabilitation and CVD Prevention, which include specific recommendations for resistance training in cardiac patients. Summarized below is some background information regarding the ACSM, AHA and CACR guidelines. We direct the reader to the original documents for more detailed information (1,2,3,4), and to other articles featured in this edition of Newsbeat. Health & fitness benefits of resistance training: Both aerobic endurance exercise and resistance training can positively effect health and fitness variables. Specific benefits of resistance training are outlined below: provides an effective method for improving muscular strength and endurance in cardiac patients who may lack physical strength to perform occupational or daily activities;
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.027 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".