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Record W4213075867 · doi:10.1016/j.dib.2022.107961

Data on body mass, glucose tolerance and bone phenotype of mice with osteogenesis imperfecta on long-term low-fat and high-fat diets

2022· article· en· W4213075867 on OpenAlexafffund
Josephine T. Tauer, Iris Boraschi-Diaz, Svetlana V. Komarova

Bibliographic record

VenueData in Brief · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsMcGill UniversityShriners Hospitals for Children - Canada
FundersMitacs
KeywordsOsteogenesis imperfectaObesityEndocrinologyPhenotypeInternal medicineFat massBone massBiologyMedicinePathologyGeneticsOsteoporosisGene

Abstract

fetched live from OpenAlex

Male and female mice with a dominant severe bone fragility disorder, osteogenesis imperfecta, and their wild-type littermates (FVB background) were challenged with a long-term (26 weeks) high-fat diet to evaluate the development of obesity and glucose intolerance. Here we present data for the measurements of body mass, the outcome of glucose tolerance tests during the long-term diet, as well as organ weights and bone phenotype at the end of the study. Interpretation of the data and further in-depth analysis can be found in the article "Male but not female mice with severe osteogenesis imperfecta are partially protected from high-fat diet-induced obesity." by Tauer JT, Boraschi-Diaz I, Al Rifai O, Rauch F, Ferron M, Komarova SV, published in Molecular Genetics and Metabolism. The data presented here demonstrate individual mouse outcomes of long-term diet experiments that can be reused for comparative studies of diet-induced changes in wild-type mice on different backgrounds and different mouse models of osteogenesis imperfecta.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.649

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 science0.0010.002
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 head0.020
GPT teacher head0.286
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 designBench or experimental
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

Citations1
Published2022
Admission routes2
Has abstractyes

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