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Record W2905256050 · doi:10.1123/pes.2018-0191

Measurement and Interpretation of Maximal Aerobic Power in Children

2018· review· en· W2905256050 on OpenAlexaff
Bareket Falk, Raffy Dotan

Bibliographic record

VenuePediatric Exercise Science · 2018
Typereview
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsBrock University
Fundersnot available
KeywordsVO2 maxProtocol (science)Affect (linguistics)Interpretation (philosophy)MedicineAerobic capacityAerobic exerciseModality (human–computer interaction)Physical therapyCardiovascular fitnessPhysical fitnessApplied psychologyComputer sciencePsychologyArtificial intelligenceAlternative medicinePathology

Abstract

fetched live from OpenAlex

The assessment of maximal aerobic power ( V˙O2max) in both children and adults is an invaluable tool for the evaluation of exercise performance capacity and general physical fitness in clinical, athletic, public health, and research applications. The complexity of means and considerations, as well as varying specific aims of V˙O2max testing, has prevented the formulation of a universally applicable, standard testing protocol, in general, and for children in particular. Numerous tester-controllable factors, such as exercise modality, metabolic measurement system, testing protocol, or data reduction strategies, can affect both the measurement and interpretation of V˙O2max data. Although the general guiding principles are similar, children differ from adults in several aspects. One notable difference is the frequent absence of a discernible V˙O2 plateau in children. Thus, the proper choice of equipment and procedures may be different for children than for adults. It is therefore the aim of this article to highlight the general and pediatric-specific considerations that may affect V˙O2max measurement and interpretation of results.

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)0.002
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.308
Teacher spread0.281 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations25
Published2018
Admission routes1
Has abstractyes

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