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Record W2396976941

Comparison between core temperatures measured telemetrically using the CorTemp® ingestible temperature sensor and rectal temperature in healthy Labrador retrievers.

2014· article· en· W2396976941 on OpenAlexaffabout
Stephanie Osinchuk, Susan Taylor, Cindy L. Shmon, John Pharr, John Campbell

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRectal temperatureCore temperatureCore (optical fiber)Labrador RetrieverMedicineLimits of agreementNuclear medicineSurgeryMaterials scienceAnesthesia
DOInot available

Abstract

fetched live from OpenAlex

This study evaluated the CorTemp(®) ingestible telemetric core body temperature sensor in dogs, to establish the relationship between rectal temperature and telemetrically measured core body temperature at rest and during exercise, and to examine the effect of sensor location in the gastrointestinal (GI) tract on measured core temperature. CorTemp(®) sensors were administered orally to fasted Labrador retriever dogs and radiographs were taken to document sensor location. Core and rectal temperatures were monitored throughout the day in 6 resting dogs and during a 10-minute strenuous retrieving exercise in 6 dogs. Time required for the sensor to leave the stomach (120 to 610 min) was variable. Measured core temperature was consistently higher than rectal temperature across all GI locations but temperature differences based on GI location were not significant (P = 0.5218). Resting dogs had a core temperature that was on average 0.4°C above their rectal temperature with 95% limits of agreement (LoA) between 1.2°C and -0.5°C. Core temperature in exercising dogs was on average 0.3°C higher than their concurrent rectal temperature, with LoA of +1.6°C and -1.1°C.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.060
GPT teacher head0.312
Teacher spread0.252 · 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.

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

Citations19
Published2014
Admission routes2
Has abstractyes

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