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Record W3046421369 · doi:10.1021/tx060177s

More on Molecular Mimicry in Mercury Toxicology

2006· article· en· W3046421369 on OpenAlexaffabout
Ruth E. Hoffmeyer, Satya Pal Singh, Christian J. Doonan, Ingrid J. Pickering, Graham N. George, Andrew R. S. Ross, Richard J. Hughes

Bibliographic record

VenueChemical Research in Toxicology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsNational Research Council CanadaPlant Biotechnology InstituteUniversity of Saskatchewan
Fundersnot available
KeywordsMimicryMercury (programming language)ToxicologyChemistryBiologyEnvironmental chemistryComputational biologyZoologyComputer science

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVLetters to the Edito...Letters to the EditorNEXTMore on Molecular Mimicry in Mercury ToxicologyRuth E. Hoffmeyer, Satya P. Singh, Christian J. Doonan, Ingrid J. Pickering, Graham N. George, Andrew R. S. Ross, and Richard J. HughesView Author Information Department of Geological Sciences University of Saskatchewan 114 Science Place Saskatoon, Saskatchewan S7N 5E2 Canada National Research Council Canada Plant Biotechnology Institute 110 Gymnasium Place Saskatoon, Saskatchewan S7N 0W9 CanadaCite this: Chem. Res. Toxicol. 2006, 19, 9, 1118–1120Publication Date (Web):August 18, 2006Publication History Published online18 August 2006Published inissue 1 September 2006https://doi.org/10.1021/tx060177sCopyright © 2006 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views370Altmetric-Citations5LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (33 KB) Get e-AlertscloseSUBJECTS:Conformation,Mercury,Monomers,Peptides and proteins,Solution chemistry Get e-Alerts

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 categoriesInsufficient payload (model declined to judge)
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 score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.385
Teacher spread0.330 · 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

Citations6
Published2006
Admission routes2
Has abstractyes

Explore more

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