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Management of diabetic mellitus induced nephropathy by intermittent hemodialysis in a dog

2024· article· W7140276587 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Advanced Biochemistry Research · 2024
Typearticle
Language
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsUremiaHemodialysisDiabetes mellitusUrineDiabetic nephropathyAbdominal ultrasoundUrinary system

Abstract

fetched live from OpenAlex

A 7-year-old male Labrador retriever with chronic diabetes mellitus managed on Isophane insulin was presented with lethargy, anorexia, vomiting, halitosis, melena, and weight loss since last 1 week due to recent mismanagement. Initial therapy at field level had failed to improve the dog's condition. Clinical, hemato-biochemical and routine urine evaluation revealed anemia, neutrophilia, thrombocytopenia, elevated BUN, creatinine, phosphorus, blood glucose, acidic urine (pH 6.0), proteinuria, glycosuria, and RBCs in urine. Radiography, abdominal ultrasound and cardiac echocardiography indicated mild broncho-interstitial lung pattern, hyperechoic kidneys, and left ventricular hypertrophy. Urine culture showed Escherichia coli. The dog underwent intermittent hemodialysis (IHD) for high uremia and suspected acute diabetic nephropathy. Despite significant improvements in uremia and electrolytes after three IHD sessions, the dog developed a high-grade fever and collapsed, likely due to sepsis.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
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 head0.064
GPT teacher head0.420
Teacher spread0.357 · 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