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Record W2050468835 · doi:10.1519/ssc.0b013e3181df4521

Core Training: Evidence Translating to Better Performance and Injury Prevention

2010· article· en· W2050468835 on OpenAlexaff
Stuart M. McGill

Bibliographic record

VenueStrength and conditioning journal · 2010
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTorsoTrainerCore (optical fiber)Physical medicine and rehabilitationCore stabilityFunction (biology)Computer scienceTraining (meteorology)MedicinePhysical therapyAnatomyTelecommunications

Abstract

fetched live from OpenAlex

THIS REVIEW ARTICLE RECOGNIZES THE UNIQUE FUNCTION OF THE CORE MUSCULATURE. IN MANY REAL LIFE ACTIVITIES, THESE MUSCLES ACT TO STIFFEN THE TORSO AND FUNCTION PRIMARILY TO PREVENT MOTION. THIS IS A FUNDAMENTALLY DIFFERENT FUNCTION FROM THOSE MUSCLES OF THE LIMBS, WHICH CREATE MOTION. BY STIFFENING THE TORSO, POWER GENERATED AT THE HIPS IS TRANSMITTED MORE EFFECTIVELY BY THE CORE. RECOGNIZING THIS UNIQUENESS, IMPLICATIONS FOR EXERCISE PROGRAM DESIGN ARE DISCUSSED USING PROGRESSIONS BEGINNING WITH CORRECTIVE AND THERAPEUTIC EXERCISES THROUGH STABILITY/MOBILITY, ENDURANCE, STRENGTH AND POWER STAGES, TO ASSIST THE PERSONAL TRAINER WITH A BROAD SPECTRUM OF CLIENTS.

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)0.008
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0210.001

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 head0.326
Teacher spread0.293 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations316
Published2010
Admission routes1
Has abstractyes

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Same venueStrength and conditioning journalSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207