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Record W3014084780

Relationship of fat composition of throwing skill between the male cricket Player

2017· article· en· W3014084780 on OpenAlex
Sandeep Singh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Emerging Technologies and Innovative Research · 2017
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsCricketThrowingAnthropometryBody weightSkinfold thicknessComposition (language)Physical therapyMathematicsMedicineEngineeringAeronauticsBiologyArtInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to determine relationship of body composition components with the throwing skill among cricket players. Total 35 male cricket players from the various colleges affiliated to Guru Nanak Dev University, Amritsar were selected to participate in the study. The subjects were assessed for height, weight and skinfold thicknesses. Height of the subjects was measured by using the standard anthropometric rod (HG-72, Nexgen ergonomics, Canada). Body weight of the subjects was measured with the help of portable weighing machine. Skinfold thicknesses of the body parts were measured with the Harpenden skinfold caliper. Throwing skill of the cricket players was assessed by AAHPERD cricket skill test battery. The statistical analysis revealed that the height, weight, BMI, skinfold thicknesses and various components of body composition did not show significant relationship with the throwing skill among the cricket players.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.031
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.201
GPT teacher head0.457
Teacher spread0.256 · 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