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Record W2753890312 · doi:10.1002/cpmo.31

Pathology Evaluation of Developmental Phenotypes in Neonatal and Juvenile Mice

2017· article· en· W2753890312 on OpenAlexaff
Brad Bolon, Susan Newbigging, Kelli L. Boyd

Bibliographic record

VenueCurrent Protocols in Mouse Biology · 2017
Typearticle
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsToronto Centre for Phenogenomics
FundersVanderbilt University
KeywordsPhenotypeJuvenileBiologyPathologyAutopsyDiseasePhysiologyMedicineGeneticsGene

Abstract

fetched live from OpenAlex

Necropsy (or autopsy) is the post mortem dissection of an animal to examine and collect organs and tissues in order to understand the effects and causes of disease. The systematic harvesting of samples at necropsy is an essential step in defining the reason for an unexpected death and in characterizing the features (i.e., phenotype) of a newly discovered condition. Phenotypic evaluation of young (neonatal and juvenile) mice emphasizes morphologic (macroscopic and microscopic) techniques and biochemical (clinical chemistry, hematologic, and molecular) analyses. This paper describes the most common procedures utilized to gather phenotypic data from neonatal and juvenile mice, with advanced alternatives for preparing special specimens (e.g., blood smears, electron microscopic samples). These techniques are applicable to young mice of all strains and are effective regardless of the fundamental cause, including genetically engineered or spontaneous mutations and exposure to pathogens or xenobiotic agents (i.e., foreign chemicals). © 2017 by John Wiley & Sons, Inc.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.278
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.329
GPT teacher head0.498
Teacher spread0.168 · 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 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

Citations6
Published2017
Admission routes1
Has abstractyes

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