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Record W2366488966 · doi:10.1136/vetreccr-2016-000304

Multiple myeloma in a dog: a typical presentation with an atypical serum protein electrophoretogram

2016· article· en· W2366488966 on OpenAlexaboutno aff
Tracy Lindquist, Austin K. Viall, Ilyssa L. Meren, Heather A. Flaherty

Bibliographic record

VenueVeterinary Record Case Reports · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSerum protein electrophoresisMultiple myelomaPathologyHistopathologyProteinuriaOsteolysisBence Jones proteinBone marrowBiopsyUrinalysisAnatomyRadiologyInternal medicineImmunoglobulin light chainUrinary systemKidneyAntibodyMonoclonal

Abstract

fetched live from OpenAlex

A nine‐year‐old spayed female labrador retriever presented with marked paraparesis. Radiographic imaging revealed regions of osteolysis within the spinous process of the L1 vertebra and the lamina and pedicles of the T13 vertebra. Cytological examination of the bone marrow exhibited a marked increase in plasma cells; histopathology of a core needle biopsy from the L1 spinous process revealed normal bone marrow findings with only scattered plasma cells. The serum biochemical profile demonstrated multiple abnormalities, some of which are frequently observed in cases of multiple myeloma such as hypercalcaemia and hyperglobulinemia. Initial serum protein electrophoresis (SPE) exhibited a tall, narrow peak of the β‐1 region superimposed onto a broad total β globulin base. The SPE also demonstrated a second α‐2 spike and low γ fraction. Although a urinalysis revealed a significant proteinuria, the patient lacked a Bence Jones proteinuria. The combined diagnostic workup was consistent with multiple myeloma.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.035
GPT teacher head0.326
Teacher spread0.291 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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