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Record W4282561895 · doi:10.1177/01926233221101314

Society of Toxicologic Pathology Neuropathology Interest Group Article: Neuropathologic Findings in Nonhuman Primates Associated With Administration of Biomolecule-Based Test Articles

2022· article· en· W4282561895 on OpenAlexaff
Dinesh S. Bangari, Lisa G. Lanigan, Félix Goulet, Sílvia Sisó, Brad Bolon

Bibliographic record

VenueToxicologic Pathology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotoxicology and immune responses
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsNeuropathologyCentral nervous systemNeuroscienceNervous systemMedicineSystemic administrationBystander effectDruggabilityPathologyBiologyImmunologyDiseaseGeneIn vivo

Abstract

fetched live from OpenAlex

The increasing specificity of novel druggable targets coupled with the complexity of emerging therapeutic modalities for treating human diseases has created a growing need for nonhuman primates (NHPs) as models for translational drug discovery and nonclinical safety assessment. In particular, NHPs are critical for investigating potential unexpected/undesired on-target and off-target liabilities associated with administration of candidate biotherapeutics (nucleic acids, proteins, viral gene therapy vectors, etc.) to treat nervous system disorders. Nervous system findings unique to or overrepresented in NHPs administered biomolecule-based ("biologic") test articles include mononuclear cell infiltration in most neural tissues for all biomolecule classes as well as neuronal necrosis with glial cell proliferation in sensory ganglia for certain viral vectors. Such test article-related findings in NHPs often must be differentiated from procedural effects (e.g., local parenchymal or meningeal reactions associated with an injection site or implanted catheter to administer a test article directly into the central nervous system) or spontaneous background findings (e.g., neuronal autophagy in sensory ganglia).

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.246
Teacher spread0.222 · 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.

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

Citations9
Published2022
Admission routes1
Has abstractyes

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