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Record W4389953686 · doi:10.1111/vde.13222

Abstracts of the scientific communications presented at the 34th European Veterinary Dermatology Congress Organized by ESVD‐ECVD, Gothenburg, Sweden, 31 August–2 September 2023

2023· article· en· W4389953686 on OpenAlexfundno aff

Bibliographic record

VenueVeterinary Dermatology · 2023
Typearticle
Languageen
FieldVeterinary
TopicInfectious Diseases and Mycology
Canadian institutionsnot available
FundersInstitute of GeneticsUniversity of BernUniversity of Pennsylvania
KeywordsMedicineLibrary scienceVeterinary medicineFamily medicinePolitical scienceComputer science

Abstract

fetched live from OpenAlex

Intralymphatic immunotherapy (ILIT) has been successfully used in both human and veterinary medicine for years and has emerged as a symptom-reducing and safe immune treatment for allergic diseases.Initially, ILIT was mostly administered by ultrasound guidance in the lymph nodes as described in human studies, and palpation-based injections became more popular among veterinary surgeons.However, human data show that precise injection into the lymph node is mandatory and injection quality clearly correlates with clinical response.The aim of this study was to assess whether the injection method (by ultrasound guidance versus palpation-based) correlated with clinical response in canine atopic dermatitis (cAD) patients.A total of 129 CAD cases treated with ILIT between 2014 and 2022 were retrieved from the hospital clinical database.Included dogs had to have received at least three intralymphatic injections administered either by palpation (PB-ILIT) or ultrasound guidance (U-ILIT).Those cases were retrospectively assessed and compared regarding clinical response to ILIT.Of 109 dogs, 84 received U-ILIT and 25 received PB-ILIT.Significantly more dogs responded to U-ILIT (60.7%) than PB-ILIT (28%).As described in human medicine, this study confirms that positive clinical response seems to depend on successful ILIT injections and low-quality injections must be acknowledged as a possible reason for ILIT failure in dogs.Further prospective and controlled studies are necessary to confirm these results.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.333
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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2023
Admission routes1
Has abstractyes

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