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Record W2273842523 · doi:10.1186/s12983-016-0141-5

How to build your dragon: scaling of muscle architecture from the world’s smallest to the world’s largest monitor lizard

2016· article· en· W2273842523 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Zoology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaRoyal Veterinary CollegeCompany of BiologistsSimon Fraser UniversityHarvard University
KeywordsBiologyLizardArchitectureBiodiversityScalingEcologyArchaeologyMathematicsGeography

Abstract

fetched live from OpenAlex

BACKGROUND: The functional design of skeletal muscles is shaped by conflicting selective pressures between support and propulsion, which becomes even more important as animals get larger. If larger animals were geometrically scaled up versions of smaller animals, increases in body size would cause an increase in musculoskeletal stress, a result of the greater scaling of mass in comparison to area. In large animals these stresses would come dangerously close to points of failure. By examining the architecture of 22 hindlimb muscles in 27 individuals from 9 species of varanid lizards ranging from the tiny 7.6 g Varanus brevicauda to the giant 40 kg Varanus komodoensis, we present a comprehensive dataset on the scaling of musculoskeletal architecture in monitor lizards (varanids), providing information about the phylogenetic constraints and adaptations of locomotor muscles in sprawling tetrapods. RESULTS: Scaling results for muscle mass, pennation and physiological cross-sectional area (PCSA), all suggest that larger varanids increase the relative force-generating capacity of femur adductors, knee flexors and ankle plantarflexors, with scaling exponents greater than geometric similarity predicts. Thus varanids mitigate the size-related increases in stress by increasing muscle mass and PCSA rather than adopting a more upright posture with size as is shown in other animals. As well as the scaling effects of muscle properties with body mass, the variation in muscle architecture with changes in hindlimb posture were also prominent. Within varanids, posture varies with habitat preference. Climbing lizards display a sprawling posture while terrestrial lizards display a more upright posture. Sprawling species required larger PCSAs and muscle masses in femur retractors, knee flexors, and ankle plantarflexors in order to support the body. CONCLUSIONS: Both size and posture-related muscle changes all suggest an increased role in support over propulsion, leading to a decrease in locomotor performance which has previously been shown with increases in size. These estimates suggest the giant Pleistocene varanid lizard (Varanus megalania priscus) would likely not have been able to outrun early humans with which it co-habitated the Australian landmass with.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.946

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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