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Record W2328517511 · doi:10.1097/nt.0b013e3182978809

Switching Habitual Small and Large Volume Drinkers

2013· article· en· W2328517511 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

VenueNutrition Today · 2013
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsEmployment and Social Development Canada
Fundersnot available
KeywordsThirstVasopressinArginineEndocrinologyInternal medicineFluid intakeHormoneDehydrationChemistryMedicinePhysiologyBiochemistry

Abstract

fetched live from OpenAlex

Normal human water intake spans a large range owing to the body’s ability to excrete large volumes of water in times of excess and conserve in times of scarcity. Recently, chronic intakes of either large volumes (HIGH) or small volumes (LOW) of water have been investigated. Adaptations within the renal regulation of water through the secretion and reabsorptive actions of the hormone arginine vasopressin and the thirst mechanism have been observed to differentiate these 2 groups during normal living. Increases or decreases in daily fluid intake in LOW and HIGH resulted in appropriate arginine vasopressin and perception of thirst changes, which enabled fluid balance in both of these populations. However, future research should establish if the chronic adaptive mechanisms, by which fluid is regulated have long-term negative outcomes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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