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The Peculiarities of Physical Fitness Test System of the British Armed Forces

2023· article· en· W4380876272 on OpenAlexaff
Олександр Петрачков, Serhii Zhembrovskyi

Bibliographic record

VenueScientific Journal of National Pedagogical Dragomanov University Series 15 Scientific and pedagogical problems of physical culture (physical culture and sports) · 2023
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsCanadian Armed Forces
Fundersnot available
KeywordsPhysical fitnessTest (biology)PreparednessProcess (computing)Fitness testMilitary personnelApplied psychologyOperations researchPsychologyComputer scienceEngineeringMedicinePhysical therapyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The article examines the optimization of Physical Fitness Test System of the British Armed Forces based on the experience of conducting combat operations in military conflicts of the 21st century. Scientific researches, justifications and experience of implementing of modern approaches of the implementation of Physical Fitness Test System of commissioned officers were analysed. This Test System takes into account phased testing of physical fitness levels, suitability and preparedness in different periods of training and combat activity, taking into account the specifics of professional activity, but without an emphasis on gender and age differences. The effective methods of physical fitness testing are used in the British Armed Forces. They are: the verification of educational process and indicators of the effectiveness of the developed programs, the perception and the awareness of training process in order to determine the physical condition of commissioned officers, and make changes in the training process; conducting a medical examination of servicemen with a health problems or limited functional capabilities, with subsequent allocation to medical rehabilitation groups. The purpose of the study was to analyse changes in Physical Fitness Test System of the British Armed Force and to introduce new fitness tests. Conclusions. The analysis of changes in Physical Fitness Test System of the British Armed Forces determined the idea of introducing a list of new standards that are used in the conditions of combat activity. The developed Physical Fitness system in the British Armed Forces is characterized by formation of physical readiness of commissioned officers to acquire capabilities to perform combat tasks as assigned by introducing military-applied tests into the physical training system, which are performed in the conditions of combat and training-combat activities. Also, the Physical Fitness system is characterized by step-by-step implementation of specialized tests at different stages of training, which reveals a comprehensive approach in physical fitness system; the same approaches to the regulatory framework in the test system regardless of gender and age characteristics; increasing the list of physical exercises of explosive strength and power endurance with a simultaneous decrease of aerobic endurance exercises.

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)0.006
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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.361
Teacher spread0.280 · 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

Citations16
Published2023
Admission routes1
Has abstractyes

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