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Record W2129781719 · doi:10.1002/ar.23201

Drifting Diaphyses: Asymmetry in Diametric Growth and Adaptation Along the Humeral and Femoral Length

2015· article· en· W2129781719 on OpenAlexaff
Isabel S. Maggiano, Corey Maggiano, Vera Tiesler, Julio Roberto Chi-Keb, Sam D. Stout

Bibliographic record

VenueThe Anatomical Record · 2015
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsWestern UniversityUniversity of Saskatchewan
FundersDeutsche Forschungsgemeinschaft
KeywordsDiaphysisHumerusFemurAnatomyCortical boneBiologyPaleontology

Abstract

fetched live from OpenAlex

This study quantifies regional histomorphological variation along the human humeral and femoral diaphysis in order to gain information on diaphyseal growth and modeling drift patterns. Three thin sections at 40, 50, and 60% bone length were prepared from a modern Mexican skeletal sample with known age and sex to give a longitudinal perspective on the drifting cortex (12 adults and juveniles total, 7 male and 5 female). Point-count techniques were applied across eight cross-sectional regions of interest using the starburst sampling pattern to quantify percent periosteal and endosteal primary lamellar bone at each diaphyseal level. The results of this study show a posterio-medial drift pattern in the humerus with a posterior rotational trend along the diaphysis. In the femur, we observed a consistent lateral to anteriolateral drift and an increase in primary lamellar bone area of both, periosteal and endosteal origin, towards the distal part of the diaphysis. These observations characterize drifting diaphyses in greater detail, raising important questions about how to resolve microscopic and macroscopic cross-sectional analysis towards a more complete understanding of bone growth and mechanical adaptation. Accounting for modeling drift has the potential to positively impact age and physical activity estimation, and explain some of the significant regional variation in bone histomorphology seen within (and between) bone cross-sections due to differing ages of tissue formation. More study is necessary, however, to discern between possible drift scenarios and characterize populational variation.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.288
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.062
GPT teacher head0.333
Teacher spread0.271 · 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

Citations31
Published2015
Admission routes1
Has abstractyes

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