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Record W4239185371 · doi:10.1159/000170147

Nutritional Assessment

2008· review· en· W4239185371 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBlood Purification · 2008
Typereview
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBody waterBioelectrical impedance analysisLean body massHydrostatic weighingAnthropometryLean tissueReliability (semiconductor)Isotope dilutionMathematicsBody weightMedicineChemistryEndocrinologyInternal medicineBody mass indexPhysics

Abstract

fetched live from OpenAlex

Measurements of body composition are made to assess nutritional status. The measurements used for these studies should be selected on the basis of reliability, as well as simplicity and costs, and reliability depends on the information required. In normal adults simple estimates of fat and lean tissue (LBM), i.e. the anthropometric measurements of weight, height and skin fold thickness, should be sufficient since the proportions, in LBM, of water, protein and bone mineral are relatively constant. Measurements of body water (by isotope dilution or bioelectrical impedance) allow indirect estimates of fat and LBM that are reliable, provided that water is a constant proportion of LBM. In disease states, however, including renal disease, it is well established that the proportion of water in LBM varies from significant water overload to dehydration. In disease, it is important to determine not only total LBM but also the quality of LBM, determining essential body protein as well as body water. Body protein can be measured directly by nuclear techniques. This procedure should be more readily available for the clinical investigation of nutritional status.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.093
GPT teacher head0.384
Teacher spread0.290 · 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