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Record W4224020309 · doi:10.1515/ci-2022-0231

Environmental Chemistry and Sustainability

2022· article· en· W4224020309 on OpenAlexaboutno aff
Diane Purchase, Annemieke Farenhorst, Hemda Garelick, Nadia G. Kandile, Christine K. Luscombe, Laura L. McConnell, Bülent Mertoğlu, Bradley S. Miller, Fani Sakellariadou, Roberto Terzano, Weiping Wu

Bibliographic record

VenueChemistry International · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityIndustrial chemistryChemistryEnvironmental scienceEnvironmental chemistryBiochemical engineeringEngineeringEcologyBiology

Abstract

fetched live from OpenAlex

The 48th IUPAC World Chemistry Congress and the Canadian Chemistry Conference took place virtually on 15-20 August 2021. Oral presentations were uploaded in advance to be viewed on-demand; they were complemented by live discussion sessions with the speakers during the conference. The IUPAC Chemistry and the Environment Division (Division VI), also supported by the Polymer Division (Division IV), organized four symposia on Environmental Chemistry and Sustainability in the ‘Chemistry and Sustainability’ thematic programme. The symposia provided forums to share advanced knowledge on environmental chemistry, the connectivity between environmental chemistry and the UN Sustainable Development Goals, and improved technologies for safeguarding different environmental compartments and human health. For example, the next generations of sustainable polymers, the identification and impact of pollutants in the atmospheric, aquatic and terrestrial ecosystems caused by fires, and the innovation of sustainable applications in crop and livestock agricultural production

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)0.004
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.011
Scholarly communication0.0090.005
Open science0.0010.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0350.007

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 head0.002
GPT teacher head0.172
Teacher spread0.170 · 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
GenreReview

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

Citations0
Published2022
Admission routes1
Has abstractyes

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