MétaCan
Menu
Back to cohort
Record W4312944081 · doi:10.4236/ojvm.2022.1212014

Anatomical and Radiological Description of the <i>Macaca fascicularis</i> Spine in Comparison with the Human Spine

2022· article· en· W4312944081 on OpenAlexaff
Anant Krishnan, Guneet Kaleka, Scott S. Emerson, Guy Sovak, Heather A. Simmons, Kevin Brunner, Dane Schalk, John B. Sledge, Amber Hoggatt, Shanker Nesathurai

Bibliographic record

VenueOpen Journal of Veterinary Medicine · 2022
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsHamilton Health SciencesMcMaster UniversityCanadian Memorial Chiropractic College
Fundersnot available
KeywordsAnatomyMedicineLumbarLumbar spineLumbar vertebraeSurgery

Abstract

fetched live from OpenAlex

Background: This paper describes and displays the spinal radiological anatomy and associated pathology in a Macaca fascicularis and compares it to the spinal anatomy of humans. Animal models are commonly used in research. As compared to Macaca mulatta, the anatomy of M. fascicularis is less well described in the literature. Materials and methods: The authors anatomically reconstructed and reviewed the defleshed spine of a single adult M. fascicularis visually, radiographically, and with high resolution CT. Results: 7 cervical, 12 thoracic, 6 lumbar, 3 sacral, and 16 caudal vertebrae were identified. Similarities in the spine to humans were seen as well as differences such as the beaked anterior arch of C1, the anterior pointed lower lumbar vertebrae, the upward curved transverse processes, and presence of three sacral segments. Degenerative changes were seen at multiple locations similar to humans though most pronounced at T3-4. Conclusions: This paper addresses the normal spinal anatomy and degenerative changes in an adult M. fascicularis and compares it to humans.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.173
GPT teacher head0.384
Teacher spread0.211 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueOpen Journal of Veterinary MedicineSame topicVeterinary Orthopedics and NeurologyFrench-language works237,207