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Record W2072706645 · doi:10.1111/joa.12041

Fundamental ratios and logarithmic periodicity in human limb bones

2013· article· en· W2072706645 on OpenAlexaff
Alexis Pietak, Siyan Ma, Caroline W. Beck, Mark D. Stringer

Bibliographic record

VenueJournal of Anatomy · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital limb and hand anomalies
Canadian institutionsQueen's University
FundersNational Institutes of HealthUniversity of Otago
KeywordsUlnaHumerusTibiaFemurAnatomyUpper limbLong boneLower limbBiomechanicsMedicineSurgery

Abstract

fetched live from OpenAlex

Fundamental mathematical relationships are widespread in biology yet there is little information on this topic with regard to human limb bone lengths and none related to human limb bone volumes. Forty-six sets of ipsilateral upper and lower limb long bones and third digit short bones were imaged by computed tomography. Maximum bone lengths were measured manually and individual bone volumes calculated from computed tomography images using a stereologic method. Length ratios of femur : tibia and humerus : ulna were remarkably similar (1.21 and 1.22, respectively) and varied little (<7%) between individuals. The volume ratio of femur : tibia was approximately half that of humerus : ulna (1.58 and 3.28, respectively; P < 0.0001). Lower limb bone volume ratios varied much more than upper limb ratios. The relationship between bone length and volume was found to be well described by power laws, with R(2) values ranging from 0.983 to 0.995. The most striking finding was a logarithmic periodicity in bone length moving from distal to proximal up the limb (upper limb λ = 0.72, lower limb λ = 0.93). These novel data suggest that human limb bone lengths and volumes follow fundamental and highly conserved mathematical relationships, which may contribute to our understanding of normal and disordered growth, stature estimation, and biomechanics.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.205

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 head0.005
GPT teacher head0.241
Teacher spread0.236 · 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

Citations42
Published2013
Admission routes1
Has abstractyes

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