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Record W2733689757 · doi:10.1016/j.bonr.2017.06.002

Lacunar-canalicular network in femoral cortical bone is reduced in aged women and is predominantly due to a loss of canalicular porosity

2017· article· en· W2733689757 on OpenAlexafffund
Amir M. Ashique, Lori S. Hart, C. David L. Thomas, John G. Clement, Peter Pivonka, Y. Carter, Darrell D. Mousseau, David M. L. Cooper

Bibliographic record

VenueBone Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchSaskatchewan Health Research Foundation
KeywordsOsteocyteCortical boneBone canaliculusConfocal laser scanning microscopyBone remodelingAnatomyReduction (mathematics)BiologyChemistryBiophysicsEndocrinologyOsteoblast

Abstract

fetched live from OpenAlex

= 6) healthy women donors utilizing a fluorescent labelling technique in combination with confocal laser scanning microscopy. A large cross-sectional area of cortical bone spanning the endosteal to periosteal surfaces from the anterior proximal femoral shaft was examined in order to account for potential trans-cortical variation in the LCN. Overall, we found that LCN areal fraction was reduced by 40.6% in the samples from aged women. This reduction was due, in part, to a reduction in lacunar density (21.4% decline in lacunae number per given area of bone), but much more so due to a 44.6% decline in canalicular areal fraction. While the areal fraction of larger vascular canals was higher in endosteal vs. periosteal regions for both age groups, no regional differences were observed in the areal fractions of the LCN and its components for either age group. Our data indicate that the LCN is diminished in aged women, and is largely due to a decline in the canalicular areal fraction, and that, unlike vascular canal porosity, this diminished LCN is uniform across the cortex.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.049
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.022
GPT teacher head0.328
Teacher spread0.305 · 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

Citations74
Published2017
Admission routes2
Has abstractyes

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