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Record W4362696797 · doi:10.1016/j.cbpa.2023.111422

Patterns of energy allocation during energetic scarcity; evolutionary insights from ultra-endurance events

2023· article· en· W4362696797 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

VenueComparative Biochemistry and Physiology Part A Molecular & Integrative Physiology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Physical Performance
Canadian institutionsWestern University
Fundersnot available
KeywordsScarcityPerspective (graphical)Energy (signal processing)EcologyEvolutionary theoryBiologyData scienceCognitive psychologyPsychologyComputer scienceEconomicsArtificial intelligenceMicroeconomicsEpistemology

Abstract

fetched live from OpenAlex

Exercise physiologists and evolutionary biologists share a research interest in determining patterns of energy allocation during times of acute or chronic energetic scarcity. Within sport and exercise science, this information has important implications for athlete health and performance. For evolutionary biologists, this would shed new light on our adaptive capabilities as a phenotypically plastic species. In recent years, evolutionary biologists have begun recruiting athletes as study participants and using contemporary sports as a model for studying evolution. This approach, known as human athletic palaeobiology, has identified ultra-endurance events as a valuable experimental model to investigate patterns of energy allocation during conditions of elevated energy demand, which are generally accompanied by an energy deficit. This energetic stress provokes detectable functional trade-offs in energy allocation between physiological processes. Early results from this modelsuggest thatlimited resources are preferentially allocated to processes which could be considered to confer the greatest immediate survival advantage (including immune and cognitive function). This aligns with evolutionary perspectives regarding energetic trade-offs during periods of acute and chronic energetic scarcity. Here, we discuss energy allocation patterns during periods of energetic stress as an area of shared interest between exercise physiology and evolutionary biology. We propose that, by addressing the ultimate "why" questions, namely why certain traits were selected for during the human evolutionary journey, an evolutionary perspective can complement the exercise physiology literature and provide a deeper insight of the reasons underpinning the body's physiological response to conditions of energetic stress.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.013
GPT teacher head0.249
Teacher spread0.237 · 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