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Record W3128216597 · doi:10.1021/cen-09904-polcon1

US to join HFC treaty

2021· article· en· W3128216597 on OpenAlex
CHERYL HOGUE

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueC&EN Global Enterprise · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJoin (topology)TreatyPolitical scienceBusinessComputer scienceComputer securityLawMathematics

Abstract

fetched live from OpenAlex

US president Joe Biden’s recent executive order on climate change includes provisions impacting a class of commercial chemicals and, likely, chemical plants. Biden called for the US to officially join a key environmental treaty controlling a class of synthetic greenhouse gases. The pact ramps down the production and use of hydrofluorocarbons (HFCs), which are used as refrigerants, solvents, and etching agents in silicon chip manufacturing. HFCs replaced two types of chemicals that erode stratospheric ozone—chlorofluorocarbons and hydrochlorofluorocarbons. While HFCs don’t harm the ozone layer, they are potent greenhouse gases. The HFC treaty, reached in 2016 in Rwanda’s capital city, is the Kigali Amendment to the 1989 Montreal Protocol on Substances That Deplete the Ozone Layer. The US signed the Kigali deal but is not yet an official treaty partner. For that to happen, the Senate must give its advice and consent. Biden directed Secretary of State Antony Blinken to formally

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.313
Teacher spread0.299 · 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