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Record W4380481982 · doi:10.6000/1929-4409.2020.09.251

Features of Physical Development of Schoolchildren in the Conditions of Specialized Training

2022· article· en· W4380481982 on OpenAlexvenueno aff
Elena Khorolskaya, Tatyana Pogrebnyak, Irina Sagalaeva, Marina N. Komarova, Natalya S. Goncharova, Natalya A. Sopina

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Training Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOvertrainingMedicineCadetCardiologyInternal medicineTachycardiaInotropePsychologyPhysical therapyAthletes

Abstract

fetched live from OpenAlex

The article presents a comparative analysis of physical development of 13-year-olds and cadet basic profile of teaching in urban schools in the parameters of somatometry and visiometry characterizing physical development, functional state, adaptation of the heart and body to current training loads. Coming of puberty is marked by intense growth of the body with heterochronous changes in the proportions and dimensions of its muscular skeletal system and the structure of internal organs. During this period, the role of mechanisms for self-regulation of heart activity and, in general, autonomous regulation of the functions of the cardiovascular system increases. At the initial stage in adolescents the manifestation of tachycardia and cardiac type of self-regulation of blood circulation increases. It is accompanied with deterioration in inotropic function of the myocardium against the background of a pronounced effect of sympatotonia and vagotonia on the systolic function of the myocardium.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.180
GPT teacher head0.490
Teacher spread0.310 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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