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Record W155290800 · doi:10.1002/9781444300635.ch2

Adaptations to Training

2008· other· en· W155290800 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Physical Performance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEndurance trainingAdaptation (eye)Strength trainingTraining (meteorology)Adaptive responseAthletesPhysiological AdaptationsPhysical medicine and rehabilitationMedicinePsychologyPhysical therapyBiologyNeuroscience

Abstract

fetched live from OpenAlex

This chapter contains sections titled: Introduction Practical considerations The future of fatigue Muscle perfomance adaptations to training Neural adaptations to training Muscular adaptations to training Objectives of training for enhancing athletic performance The training stimulus, response, and adaptation continuum Metabolic adaptations to endurance training Time-course of adaptive changes in skeletal muscle Goals of a strength training program Metabolic adaptations to strength training Performance adaptations to strength and endurance training Can strength training improve endurance performance? Sympatoadrenergic responses Growth hormone and insulin-like growth factor-I Insulin and glucagon Reproductive hormones ACTH and cortisol Cytokines Conclusions: Endocrine adaptations to training in athletes Adaptation of bone to training Principles of skeletal adaptation to training Recommendations for improving bone strength through exercise Adaptation of connective tissue to training Adaptation of a tendon to training Adaptation of a ligament to training Conclusions References

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.049
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.024
GPT teacher head0.252
Teacher spread0.229 · 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

Quick stats

Citations3
Published2008
Admission routes1
Has abstractyes

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