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Record W4255623231 · doi:10.1007/978-1-60761-401-2

Immunotoxicity Testing

2009· book· en· W4255623231 on OpenAlexfundno aff

Bibliographic record

VenueMethods in molecular biology · 2009
Typebook
Languageen
FieldImmunology and Microbiology
TopicImmunotoxicology and immune responses
Canadian institutionsnot available
FundersState University of New York Upstate Medical UniversityCollege of Veterinary Medicine, Cornell UniversitySchool of Medicine, New York UniversityUniversiteit UtrechtUniversità degli Studi di MilanoBristol-Myers SquibbYork UniversityWest Virginia UniversitySchool of Medicine, Virginia Commonwealth UniversityVirginia Commonwealth UniversitySchool of Medicine, University of South CarolinaState University of New YorkUniversity of South CarolinaPfizerEast Carolina UniversityColgate-Palmolive CompanySyracuse University
KeywordsImmunotoxicologyRisk analysis (engineering)Engineering ethicsEngineeringMedicineImmunologyImmune system

Abstract

fetched live from OpenAlex

Recent critical advances in the field of immunotoxicology have led to incredible contributions to basic science, including crucial improvements in human risk assessment. In Immunotoxicity Testing: Met

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0640.051

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 head0.029
GPT teacher head0.369
Teacher spread0.339 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations16
Published2009
Admission routes1
Has abstractyes

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