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Record W3178944398 · doi:10.1016/j.isci.2021.102777

A community based PFAS phytoremediation project at the former Loring Airforce Base

2021· article· en· W3178944398 on OpenAlexaboutno aff
Sara L. Nason, Chelli Stanley, Chief E. PeterPaul, Maggie Blumenthal, Nubia Zuverza‐Mena, Richard Silliboy

Bibliographic record

VenueiScience · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsnot available
FundersU.S. Department of Agriculture
KeywordsPhytoremediationBase (topology)World Wide WebComputer scienceEnvironmental chemistryChemistryMathematicsHeavy metals

Abstract

fetched live from OpenAlex

Protecting the land is part of the Micmac beliefs. Anything we can do to contribute to making the environment better, we want to be a part of.I heard a specific request/demand from a resident of a PFAS affected town asking scientists to step in, claiming that we were the ones who knew and had the equipment to do something about it. That made me feel powerless and realized that in a way she was speaking to people like me. Unfortunately, analyzing PFAS is complicated and removing them from the environment even more so; scientists do not have all the answers.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0100.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.065
GPT teacher head0.313
Teacher spread0.248 · 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 designObservational
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

Citations14
Published2021
Admission routes1
Has abstractyes

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