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Record W3208027164 · doi:10.5281/zenodo.3653161

S46 | PFASNTREV19 | List of PFAS reported in Non-Target HRMS Studies (Liu et al 2019)

2019· dataset· en· W3208027164 on OpenAlexaff
Lisa A. D’Agostino, Emma Schymanski, Jonathan Martin

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

List of PFAS (per- and polyfluoroalkyl substances) compiled in the non-target high resolution mass spectrometry (HRMS) PFAS review by Liu et al 2019, DOI: 10.1016/j.trac.2019.02.021. MS-ready list prepared by Yanna Liu, Lisa D'Agostino, Emma Schymanski and Jon Martin. Note not all entries have structures. Dataset DOI: 10.5281/zenodo.2656744 Update Feb 6, 2020: minor SMILES corrections to CSV for PubChem upload.

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)0.000
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0440.003

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 head0.123
GPT teacher head0.426
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations4
Published2019
Admission routes1
Has abstractyes

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