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Record W4417339716 · doi:10.1080/10408444.2025.2580643

Response to letter to the editor on: “the use of canonical dose–response models for benchmark dose analysis of continuous toxicological data”

2025· article· en· W4417339716 on OpenAlexafffund
Wout Slob, Guangchao Chen, Martine Bakker, Bas Bokkers, Weihsueh A. Chiu, Wim Mennes, Mioara Alina Nicolaie, R. Woodrow Setzer, Paul A. White

Bibliographic record

VenueCritical Reviews in Toxicology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsHealth Canada
FundersHealth CanadaMinisterie van Landbouw, Natuur en VoedselkwaliteitRijksinstituut voor Volksgezondheid en MilieuMinisterie van Volksgezondheid, Welzijn en Sport
KeywordsBenchmark (surveying)Letter to the editorMEDLINE

Abstract

fetched live from OpenAlex

We thank Cortiñas et al. for providing their views on our paper on canonical dose-response models (Slob et al. 2025). Although Cortiñas et al. agree with some of the basic points of our paper, they...

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)0.004
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.102
GPT teacher head0.396
Teacher spread0.294 · 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 designNot applicable
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
Published2025
Admission routes2
Has abstractyes

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