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Record W3164195814 · doi:10.1177/00236772211018587

Hematologic and serum biochemistry reference intervals using defined ASCVP methodology for laboratory natal multimammate mice ( <i>Mastomys natalensis</i> )

2021· article· en· W3164195814 on OpenAlexaff
Brian J. Smith, Patrick W. Hanley, Ousmane Maïga, Maarit N Culbert, Marissa J Woods, Kathleen Cordova, Chad S. Clancy, David Safronetz, Heinrich Feldmann, Kyle Rosenke, Tsing-Lee Tang-Huau

Bibliographic record

VenueLaboratory Animals · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
FundersDivision of Intramural Research, National Institute of Allergy and Infectious Diseases
KeywordsMastomysPhysiologyBiologyComplete blood countMedicineInternal medicineImmunologyRodentEcology

Abstract

fetched live from OpenAlex

Complete blood count, serum chemistry values, and biological reference intervals were compared between two age groups (34–49 and 84–120 days old) of healthy male and female laboratory raised natal multimammate mice ( Mastomys natalensis). Blood was collected via cardiocentesis under isoflurane anesthesia. Data sets of machine automated complete blood counts and clinical chemistries were analyzed. Significant differences between sex and age groups of the data sets were defined. The baseline hematologic and serum biochemistry values described here can improve interpretation of laboratory research using natal multimammate mice.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.076
GPT teacher head0.290
Teacher spread0.214 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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