Valorization of Natural Cardio Trekking Trails Through Open Innovation for the Promotion of Sustainable Cross-generational Health-Oriented Tourism in the Connect2Move Project: Protocol for a Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Hiking is one of the most popular forms of exercise in the alpine region. However, besides its health benefits, hiking is the alpine activity with the highest incidence of cardiac events. Most incidents occur due to overexertion or underestimation of the physiological strain of hiking. OBJECTIVE: This project will establish a standardized cardio trekking test trail to evaluate the exercise capacity of tourists within hiking areas and deliver a tool for the prevention of hiking-associated cardiac incidents. Further, individual exercise intensity for a hiking tour will be predicted and visualized in digital maps. METHODS: This cooperation study between Austria and Germany will first validate a 1-km outdoor cardio trekking test trail at 2 different study sites. Then, exercise intensity measures on 8-km hiking trails will be evaluated during hiking to estimate overall hiking intensity. A total of 144 healthy adults (aged >45 years) will perform a treadmill test in the laboratory and a 1-km hiking test outdoors. They will wear a portable spirometry device that measures gas exchange, as well as heart rate, walking speed, ventilation, GPS location, and altitude throughout the tests. Estimation models for exercise capacity based on measured parameters will be calculated. RESULTS: The project "Connect2Move" was funded in December 2019 by the European Regional Development Fund (INTERREG V-A Programme Austria-Bavaria - 2014-2020; Project Number AB296). "Connect2Move" started in January 2020 and runs until the end of June 2022. By the end of April 2022, 162 participants were tested in the laboratory, and of these, 144 were tested outdoors. The data analysis will be completed by the end of June 2022, and results are expected to be published by the end of 2022. CONCLUSIONS: Individual prediction of exercise capacity in healthy individuals with interest in hiking aims at the prevention of hiking-associated cardiovascular events caused by overexertion. Integration of a mathematical equation into existing hiking apps will allow individual hiking route recommendations derived from individual performance on a standardized cardio trekking test trail. TRIAL REGISTRATION: ClinicalTrails.gov NCT05226806; https://clinicaltrials.gov/ct2/show/NCT05226806. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39038.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".