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Record W3195782861 · doi:10.1111/vop.12905

Is it necessary to wait several minutes between applications of different topical ophthalmic solutions? A preliminary study with tropicamide eye drops in healthy dogs

2021· article· en· W3195782861 on OpenAlexaboutno aff
Dikla Arad, Reut Deckel, Oren Pe’er, Maya Ross, Lionel Sebbag, Ron Ofri

Bibliographic record

VenueVeterinary Ophthalmology · 2021
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsnot available
Fundersnot available
KeywordsTropicamidePost-hoc analysisMedicineSalineEye dropPost hocAnesthesiaWashoutOphthalmologyInternal medicinePsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the efficacy of topical tropicamide when placed at different time intervals before or after a saline drop. ANIMALS STUDIED: Eight healthy Labrador and golden retriever dogs. PROCEDURES: The effect of 1% tropicamide on pupillary diameter (PD) was measured over 240 min when administered alone (control) and then 1 and 5 min prior to, or following, application of a saline drop, with 1-week washout between each of the five trials. Data were analyzed using repeated-measures ANOVA and Tukey post hoc test. RESULTS: Only 6/110 pairwise comparisons among the 5 trials were statistically significant (p ≤ .035), with post-hoc analysis showing no significant differences (p ≥ .14) between the overall means of all trials. In all five trials, maximal PD was reached 30 min after tropicamide application and maintained until 210 min for 180 min (p = .0005). CONCLUSIONS: Our results suggest that waiting 1 min between applications of different ophthalmic solutions may be sufficient for maximal drug effect. Care should be taken when extrapolating these results to other species and different ophthalmic formulations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.027
Threshold uncertainty score0.983

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 head0.060
GPT teacher head0.348
Teacher spread0.288 · 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.

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

Citations6
Published2021
Admission routes1
Has abstractyes

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