MétaCan
Menu
Back to cohort
Record W2590879602 · doi:10.1186/s12917-017-0974-y

A prospective follow up of age related changes in the subchondral bone density of the talus of healthy Labrador Retrievers

2016· article· en· W2590879602 on OpenAlexaboutno aff
Walter Dingemanse, Magdalena Müller‐Gerbl, Ilse Jonkers, Jos Vander Sloten, Henri van Bree, Ingrid Gielen

Bibliographic record

VenueBMC Veterinary Research · 2016
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsnot available
FundersAgentschap voor Innovatie door Wetenschap en Technologie
KeywordsSubchondral boneBone densitySkeleton (computer programming)MedicineDistribution (mathematics)Articular surfaceAppendicular skeletonAnatomyOsteoporosisPathologyOsteoarthritisArticular cartilage

Abstract

fetched live from OpenAlex

During growth, the skeletal structures adapt to the increased loading conditions and mature to a fully-grown skeleton. Subchondral bone density reflects the effect of long-term joint loading and it is expected to change over time. The aim of this study was to describe the long-term changes in the density distribution of the subchondral bone of the talus of healthy Labrador Retrievers in a prospective study. The subchondral bone density distribution was evaluated using computed tomographic osteoabsorptiometry (CTOAM). Visually, all joints showed very similar density distribution patterns. No significant differences in the topography of the density maxima were found between t1 and t2. The mean density, maximum density, and maximum area ratio (MAR) were significantly increased with increasing age. The subchondral bone density of the talus of healthy Labrador Retrievers increases with increasing age. It is likely an adaptive response of the subchondral bone due to increased joint loading during growth.

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)0.005
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 score0.416
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.138
GPT teacher head0.406
Teacher spread0.267 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueBMC Veterinary ResearchSame topicBone health and osteoporosis researchFrench-language works237,207