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Record W2125427602 · doi:10.1152/jappl.2000.89.2.663

Total body water and ECFV measured using bioelectrical impedance analysis and indicator dilution in horses

2000· article· en· W2125427602 on OpenAlexaff
Mariann Forro, Scott Cieslar, Gayle L. Ecker, Angela Walzak, Jay Hahn, Michael I. Lindinger

Bibliographic record

VenueJournal of Applied Physiology · 2000
Typearticle
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBioelectrical impedance analysisBody waterIndicator dilutionDilutionMedicineBiomedical engineeringCardiologyBody weightInternal medicineCardiac outputBody mass indexHemodynamicsPhysics

Abstract

fetched live from OpenAlex

The purposes of this study were 1) to determine the compartmentation of body water in horses by using indicator dilution techniques and 2) to simultaneously measure bioelectrical impedance to current flow at impulse current frequencies of 5 and 200 kHz to formulate predictive equations that could be used to estimate total body water (TBW), extracellular fluid volume (ECFV), and intracellular fluid volume (ICFV). Eight horses and ponies weighing from 214 to 636 kg had catheters placed into the left and right jugular veins. Deuterium oxide, sodium thiocyanate, and Evans blue were infused for the measurement of TBW, ECFV, and plasma volume (PV), respectively. Bioelectrical impedance was measured by using a tetrapolar electrode configuration, with electrode pairs secured above the knee and hock. Measured TBW, ECFV, and PV were 0.677 +/- 0.022, 0.253 +/- 0.006, and 0.040 +/- 0.002 l/kg body mass, respectively. Strong linear correlations were determined among measured variables that allowed for the prediction of TBW, ECFV, ICFV, and PV from measures of horse length or height and impedance. It is concluded that bioelectrical impedance analysis (BIA) can be used to improve the predictive accuracy of noninvasive estimates of ECFV and PV in euhydrated horses at rest.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.268
Teacher spread0.255 · 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 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

Citations65
Published2000
Admission routes1
Has abstractyes

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