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Coinfecção de anaplasmose e erliquiose: Relato de caso

2021· article· en· W3159575170 on OpenAlexaboutno aff
Eduardo Nascimento Sousa

Bibliographic record

VenuePubVet · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
Fundersnot available
KeywordsGynecologyMedicineMolecular biologyChemistryBiology

Abstract

fetched live from OpenAlex

The ehrlichiosis and anaplasmosis’ co-infection is awfully common to the clinical routine of small animals. They’re mainly transmitted by the Rhipicephalus sanguineous tick and induce severe clinical symptoms, which are deadly able to lead specific animals to their death. A dog of the Labrador Breed was cared with 1.6-years-old male, weighing 30 kg and residing in Codó City, State of Maranhão, Brazil. In the anamnesis, it was reported that the dog was apathetic and without eat for few days, showing signs of weight loss and reddish spots. On clinical examination, the animal presented hyperthermia, pale and ocular mucous membranes, lethargic ineptitude, 8% of dehydration and capillary filling time greater than 5 seconds. Nevertheless, the animal doesn’t showed changes in the heart rate, breathing movements and lymph nodes. For diagnosis, a rapid test was performed for Anaplasma and Ehrlichia in which were positive. Complete blood count, hepatic and renal serum biochemistry and urinalysis were also applied. The laboratory exams’ results were suggestive for the diagnosis of co-infection by Anaplasma spp. and Ehrlichia spp, confirming the rapid test results. After diagnosis, supportive treatment with fluid therapy, B complex, dexamethasone, doxicillin and iminocard was started. The treatment was efficient. Therefore, the animal was clinically healthy after 25 days of treatment.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.244
Teacher spread0.234 · 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 designCase report
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

Citations4
Published2021
Admission routes1
Has abstractyes

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