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Change in intraocular pressure during maturation in Labrador Retriever dogs

2004· article· en· W1978677036 on OpenAlexaboutno aff
Albert J. Mughannam, Cynthia S. Cook, Curtis L. Fritz

Bibliographic record

VenueVeterinary Ophthalmology · 2004
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsIntraocular pressureLabrador RetrieverMedicineElevated intraocular pressureOphthalmologySignificant differenceSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To measure intraocular pressure (IOP) in a group of dogs as puppies and young adults to determine if there is any change during maturation. Animals studied Thirty-two healthy Labrador Retriever dogs. PROCEDURES: Intraocular pressure was measured using a Tonopen XL initially at approximately 6 weeks of age (T1), then again approximately 1 year later (T2). Exact ages were known based on whelp date. RESULTS: The dogs had marginally higher IOP OU at T2 (mean = 14.9 mmHg) compared to T1 (mean = 13.4 mmHg). However, the difference was not statistically significant. No differences were seen based on sex and litter. Intraocular pressure OD was statistically greater than OS at T1 but not at T2. CONCLUSIONS: Normal values for intraocular pressure are the same in puppies and adults. The results of this study do not support the previously suggested theory that younger dogs have sustained increased IOP as a requirement to drive growth of the globe. However, it does not rule out the possibility that a dynamic relationship between intraocular pressure and expansion of the globe may exist.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
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 head0.028
GPT teacher head0.301
Teacher spread0.273 · 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

Citations18
Published2004
Admission routes1
Has abstractyes

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