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Record W2802200123 · doi:10.14529/hsm170309

BIOMECHANICAL CHARACTERISTICS OF MUSCULAR AND POSTURAL REGULATION OF CONDITIONALLY LIGHTWEIGHT WEIGHTLIFTERS DURING THE BASIC PERIOD OF TRAINING

2017· article· en· W2802200123 on OpenAlexaff
А. П. Исаев, В. В. Эрлих, А. В. Ненашева, N Kleshchenkova, KukkhAbdulRahmanAhmedMosa

Bibliographic record

VenueHuman Sport Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhysical medicine and rehabilitationMuscle groupPhysical strengthExtensor muscleMuscle strengthKnee flexionJoint (building)BiomechanicsBody weightPhysical therapyMedicineAnatomyStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Aim: to assess speed-strength motor capacity of flexors and extensors of knee and hip joints, angles of force applications, and muscular performance in weightlifters. Materials and Methods. Polydynamometer produced by Biodex (USA) allows the basic, comparative, and graphic assessment of joint indicators of the upper and lower limbs (flexion-extension) at an angular speed of 150,120,920 deg/s. We examined 6 weightlifters (body weight 63.00±0.98 kg; body length 173.00±1.75 cm) qualified as Candidates for Master of Sport (n=4) and Master of Sport (n=2), aged 18.22±1.74. Results. Integrative assessment of isokinetic testing revealed that desyncrhonization and imbalance of statokinetic stability starts from the muscle system, its angular, temporal, and rotation characteristics, range of movement, dynamical instability of joints, and receptor ratio of groups of muscles participating in motor actions. These integrations are the trigger that leads to disturbances in supporting systems and shifts in indicators as seen from the comparison of involved and uninvolved elements, joint flexion and extension, and deficiency. Conclusion. The used diagnostic equipment allows the determination of muscular imbalance, assessment of structural and physiological capacity, and estimate biomechanical features including differentiation of efforts at various angular accelerations and force application.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.225
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.282
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations1
Published2017
Admission routes1
Has abstractyes

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