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Record W2791304947 · doi:10.1177/0023677218764768

Malignant lymphoma with middle ear involvement in a Sprague-Dawley rat

2018· article· en· W2791304947 on OpenAlexaff
J. Lafond, A. Landry

Bibliographic record

VenueLaboratory Animals · 2018
Typearticle
Languageen
FieldMedicine
TopicEar and Head Tumors
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsMiddle earMeningesPathologyTemporal boneLymphomaAnatomyMedicineBone marrowCranial cavityDura materDorsumCranial nerves

Abstract

fetched live from OpenAlex

Sprague-Dawley rats are amongst the most widely used animals in biomedical research and malignant lymphoma has long been known to be a frequent neoplasm in these animals. A 9-month-old male control Sprague-Dawley rat from a toxicity study showed gelatinous material in the cranial cavity and dark, thickened cerebral meninges at necropsy. At microscopic evaluation of the temporal bone, neoplastic lymphocytes were seen invading several structures of the middle ear. The neoplastic cells appeared to extend from the marrow of the temporal bone, covered the dorsal part of the tympanic cavity wall, and surrounded and infiltrated the base of the tensor tympani muscle as well as the chorda tympani branch of the facial nerve. The lymphoma was generalized; neoplastic lymphocytes were also noted in numerous other tissues. Literature regarding neoplasms of the middle and inner ear in animals is scarce and, to our knowledge, this is the first report of a lymphoma involving the middle ear of a rat.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.262
Teacher spread0.237 · 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 designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

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