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Record W2760861879 · doi:10.1080/02701367.2017.1371546

Children’s Aerobic Trainability and Related Questions

2017· article· en· W2760861879 on OpenAlexaff
Raffy Dotan

Bibliographic record

VenueResearch Quarterly for Exercise and Sport · 2017
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyAerobic exerciseDevelopmental psychologyPhysical therapyMedicine

Abstract

fetched live from OpenAlex

In response to Armstrong's recent Special Topics review of "Top 10 Research Questions Related to Youth Aerobic Fitness," this commentary revisits some of the points raised, particularly in relation to the question of whether a child‒adult trainability difference does indeed exist. Discussed are the validity of much of the existing pediatric maximal oxygen consumption data upon which trainability conclusions are drawn, why differential trainability is likely a fact rather than a doubt, a reasoned novel approach to explaining the phenomenon, and how that explanation can bear upon and answer several of the other raised questions. The commentary is intended to inspire and encourage fresh thinking not only in relation to pediatric aerobic trainability, but more generally, regarding pediatric exercise physiology and performance and how they differ from those of adults.

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)0.016
metaresearch head score (Gemma)0.074
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.074
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0040.006
Open science0.0040.004
Research integrity0.0250.027
Insufficient payload (model declined to judge)0.0050.001

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 head0.041
GPT teacher head0.379
Teacher spread0.339 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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