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Record W2145330597 · doi:10.4995/wrs.1998.349

IN VIVO MEASUREMENT OF BODY PARTS AND FAT DEPOSITION IN RABBITS BY MRI.

2010· article· en· W2145330597 on OpenAlexaff
G Kövér, Zsolt Szendrő, R. Romvárí, J.F. Jensen, Per Soelberg Sørensen, G. Milisits

Bibliographic record

VenueWorld Rabbit Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRabbits: Nutrition, Reproduction, Health
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMagnetic resonance imagingIn vivoAdipose capsule of kidneyTomographyVolume (thermodynamics)Nuclear medicineBody weightComputed tomographyMedicineAnatomyChemistryRadiologyBiologyKidneyInternal medicinePhysics

Abstract

fetched live from OpenAlex

An experiment using Magnetic Resonance lmaging (MRI) tomography were done involving 87 rabbits of four genotypes, 12 or 16 weeks old. MRI was applied on the day before slaughter. The slices were taken in three orthogonal planes. The resulting pictures indicate that MRI provides very detailed slices. The volume of the fat deposit around the kidneys, the total body fat volume of the body and the muscle of the hind part was collected from the MRI pictures. Correlation coefficients were computed between the volume of the perirenal fat and its weight, the muscle volume of the hind part and its weight, the total body fat volume and the crude fat content. The correlation values were found to be very high (0.77 to 0.94) in the group of age 16 proving that the MRI tomograph is a excellent In vivo method to determine the volumes of fat and muscle. The lower correlation values in the group of age 12 (0.39 to 0.76) indicate that the MRI tomography is sensitive to the digital sampling errors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2010
Admission routes1
Has abstractyes

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