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Record W1970683583 · doi:10.1111/jmp.12028

Abdominal ultrasonography of the normal<scp>S</scp>t.<scp>K</scp>itts vervet monkey (<i><scp>C</scp>hlorocebus sabaeus</i>)

2012· article· en· W1970683583 on OpenAlexaff
Joseph Amory, W. M. du Plessis, Amy Beierschmitt, Janet Beeler‐Marfisi, Roberta M. Palmour, Thierry Beths

Bibliographic record

VenueJournal of Medical Primatology · 2012
Typearticle
Languageen
FieldMedicine
TopicComparative Animal Anatomy Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsVervet monkeyAbdominal ultrasonographyMedicineUrinary systemUltrasonographyReproductive tractGallbladderTransrectal ultrasonographyAnatomyProstateInternal medicineBiologySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Normal ultrasonography of non-reproductive abdominal and male reproductive anatomy in the vervet monkey were prospectively assessed. This has not been previously reported. METHODS: Ten non-sexually active male and 10 non-gravid female clinically healthy vervet monkeys between 5 and 12 years of age and weighing between 3.13 and 6.85 kg were evaluated with ultrasound. Individuals were randomly divided by gender groups into one of two immobilization protocols and scanned at 18.0 MHz. RESULTS: High-quality images of the liver, gallbladder, kidneys, urinary bladder, spleen, adrenal glands, gastrointestinal tract, and testes were acquired. The prostate was never visualized. Abdominal lymph nodes other than an ileocolic, the pancreas, and the female reproductive tract were not evaluated. Gastric and duodenal motility were significantly different between immobilization protocols (P<0.05). CONCLUSIONS: Abdominal sonographic anatomy was successfully characterized and normal size parameters for non-reproductive abdominal viscera and the testes were established.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.024
GPT teacher head0.301
Teacher spread0.277 · 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 designObservational
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

Citations17
Published2012
Admission routes1
Has abstractyes

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