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Record W4327682189 · doi:10.1289/ehp12915

Erratum: Current Breast Milk PFAS Levels in the United States and Canada: After All This Time, Why Don’t We Know More?

2023· erratum· en· W4327682189 on OpenAlexaboutno aff
Judy S. LaKind, Marc-André Verner, Rachel Rogers, Helen M. Goeden, Daniel Q. Naiman, Satori A. Marchitti, Geniece M. Lehmann, Erin P. Hines, Suzanne E. Fenton

Bibliographic record

VenueEnvironmental Health Perspectives · 2023
Typeerratum
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsnot available
FundersNational Institute of Environmental Health Sciences
KeywordsBreast milkRegretLibrary scienceMedicineHistoryChemistryComputer scienceStatisticsMathematics

Abstract

fetched live from OpenAlex

During the paper editing process, two values in Table 2 were mistakenly modified.Milk:serum concentration ratios from the "Kärrman et al. 2007" study should be 0.01 for PFOS and 0.01 PFNA.This error affects values in Table 2 only.All calculations were performed with the correct values.The authors regret the error.

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)0.004
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.494

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.051
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0290.023

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 head0.016
GPT teacher head0.274
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2023
Admission routes1
Has abstractyes

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