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Record W2069761724 · doi:10.1021/es072543f

Clearing the air on ethanol | A nano Trojan horse | Perfume, perfume everywhere | News Briefs: Montreal beats Kyoto on climate controls ` Bigger fish to fry? ` Asian pollution strengthens storms ` Snapping fluorocarbon superbonds ` New aerosol source ` Snapping fluorocarbon superbonds | Perchlorate from fireworks | Seeing the forest for the methane | Thailand fuels up with cassava

2007· article· en· W2069761724 on OpenAlexaboutno aff
Erika Engelhaupt, Lizz Thrall, Barbara Booth, Rhitu Chaterjee

Bibliographic record

VenueEnvironmental Science & Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsClearingEnvironmental scienceFish <Actinopterygii>StormPollutionEnvironmental engineeringWaste managementMeteorologyEnvironmental protectionEngineeringBusinessEcologyFisheryGeographyBiology

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVNEWSNEXTClearing the air on ethanol | A nano Trojan horse | Perfume, perfume everywhere | News Briefs: Montreal beats Kyoto on climate controls ` Bigger fish to fry? ` Asian pollution strengthens storms ` Snapping fluorocarbon superbonds ` New aerosol source ` Snapping fluorocarbon superbonds | Perchlorate from fireworks | Seeing the forest for the methane | Thailand fuels up with cassavaErika Engelhaupt, Lizz Thrall, Barbara Booth, and Rhitu ChaterjeeCite this: Environ. Sci. Technol. 2007, 41, 11, 3788–3794Publication Date (Web):June 1, 2007Publication History Published online1 June 2007Published inissue 1 June 2007https://pubs.acs.org/doi/10.1021/es072543fhttps://doi.org/10.1021/es072543fnewsACS Publications. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views890Altmetric-Citations2LEARN 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 (422 KB) Get e-Alertsclose SUBJECTS:Atmospheric chemistry,Bioethanol,Climate,Fuels,Perchlorates 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 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.989
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.6980.330

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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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.

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

Citations4
Published2007
Admission routes1
Has abstractyes

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