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Record W2793378979 · doi:10.1002/rem.21547

Editor's perspective – Per‐ and polyfluorinated substances pose substantial challenges to remediation practitioners

2018· article· en· W2793378979 on OpenAlexfundaboutno aff
John Simon

Bibliographic record

VenueRemediation Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsnot available
FundersMcGill UniversityAlbert Einstein College of Medicine, Yeshiva UniversityBrown UniversityDow Chemical Company
KeywordsEnvironmental remediationEngineering ethicsComputer scienceEnvironmental planningEnvironmental scienceEngineeringEcology

Abstract

fetched live from OpenAlex

This issue of Remediation is dedicated to one of the most pressing topics in the remediation industry -per-and polyfluorinated alkylated substances (PFASs).The articles comprising the issue address critical topics in the rapidly advancing area of PFAS investigation, assessment, and remediation.

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)0.008
metaresearch head score (Gemma)0.045
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.028
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0100.009
Open science0.0040.003
Research integrity0.0220.017
Insufficient payload (model declined to judge)0.0280.016

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 head0.019
GPT teacher head0.300
Teacher spread0.280 · 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
GenreEditorial

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

Citations1
Published2018
Admission routes2
Has abstractyes

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