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Record W4394692180 · doi:10.1111/sms.14625

Reference values for leg effort during incremental cycle ergometry in non‐trained healthy men and women, aged 19–85

2024· article· en· W4394692180 on OpenAlexaff
Abed Hijleh, Sophia Wang, Danilo Cortozi Berton, Igor Neder‐Serafini, Sandra G. Vincent, Matthew D. James, Nicolle J. Domnik, Devin B. Phillips, Luíz Eduardo Nery, Denis E. O’Donnell, J. Alberto Neder

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsYork UniversityQueen's University
Fundersnot available
KeywordsMedicinePhysical therapyIncremental exercisePsychological interventionDemographyInternal medicineHeart rate

Abstract

fetched live from OpenAlex

uptake and work rate (% predicted) were used to threshold gradually higher symptom intensity categories. Leg effort-work rate increased as a function of age; women typically reported higher scores at a given age, particularly in the younger groups (p < 0.05). For instance, "heavy" (5) scores at the 95th centile were reported at ~200 W (<40 years) and ~90 W (≥70 years) in men versus ~130 W and ~70 W in women, respectively. The following categories of leg effort severity were associated with progressively lower exercise capacity: ≤50th ("mild"), >50th to <75th ("moderate"), ≥75th to <95th ("severe"), and ≥ 95th ("very severe") (p < 0.05). Although most subjects reporting peak scores <5 were in "mild" range, higher scores were not predictive of the other categories (p > 0.05). This novel frame of reference for 0-10 Borg leg effort, which considers its cumulative burden across increasingly higher exercise intensities, might prove valuable to judging symptom's normalcy, quantifying its severity, and assessing the effects of interventions in clinical populations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.017
GPT teacher head0.318
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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