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A study on psychosomatic skills among football players of University of Delhi

2024· article· en· W4402807715 on OpenAlexaboutno aff
Man Singh, Anil Kumar

Bibliographic record

VenueInternational Journal of Physical Education Sports and Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicProblem Solving Skills Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyFootballFootball playersPhysical therapyClinical psychologyMedical educationMedicinePolitical science

Abstract

fetched live from OpenAlex

The study's goal was to analyze and compare the mental abilities of selected variables, namely psychosomatic abilities, which include sub variables such as Stress Control, Relaxation, Fear Control, and Energizing, of Strikers and Midfielders of Intercollegiate Football Players at the University of Delhi. The study included a sample of 60 participants from the University of Delhi. The players were divided into two further groups: midfielders (N is the number of=30) and strikers (N is the number of=30). The current study exclusively comprised male participants. The participants' ages ranged from 18 to 25. The researcher examined strikers' and midfielders' mental profiles using a standardized technique. The researcher utilized the Ottawa Mental Skills Assessment Tool-3 (OMSAT-3 Version 2-2). The acquired data was subjected to an Independent Sample ’t’ Test, which was intended to compare. The Independent Sample ’t’ Test was used on the acquired data to compare the mental abilities selected variable, i.e., Psychosomatic abilities, of strikers and midfielders to see if there were any significant differences between the two player roles. At a significance level of 0.05, the study found no significant differences in Psychosomatic Skills (Stress Control, Relaxation, Fear Control and Energizing) between attackers and midfielders. This result was reached based on p-values from the statistical analysis that exceeded the significance level of 0.05.

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 score0.011
Threshold uncertainty score0.021

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.445
Teacher spread0.413 · 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
Published2024
Admission routes1
Has abstractyes

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