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Record W7034442330

Update on ozone-depleting substances (ODSs) and other gases of interest to the Montreal protocol

2014· other· en· W7034442330 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Repository and Bibliography (University of Liège) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal ProtocolTroposphereGreenhouse gasOzoneOzone layerChlorofluorocarbonBromineAtmosphere (unit)
DOInot available

Abstract

fetched live from OpenAlex

Changes in the global atmospheric abundance of a substance are determined by the balance between its emissions and removal. Declines observed for ozone-depleting substances (ODSs) controlled under the Montreal Protocol are due to global emission reductions that have made emissions smaller than removals. Most ODSs are potent greenhouse gases. As the majority of ODSs have been phased out, demand for hydrochlorofluorocarbon (HCFC) and hydrofluorocarbon (HFC) substitutes for the substances controlled under the Montreal Protocol has increased; these are also greenhouse gases. HCFCs deplete much less ozone per kilogram emitted than chlorofluorocarbons (CFCs), while HFCs essentially deplete no ozone. <br/><br/>\nThe amended and adjusted Montreal Protocol has continued to reduce emissions and atmospheric abundances of most controlled ozone-depleting substances. By 2012, the total combined abundance of anthropogenic ODSs in the troposphere (measured as Equivalent Chlorine) had decreased by nearly 10% from its peak value in 1994.<br/><br/>\nThe contributions to the overall decline in tropospheric chlorine (Cl) and bromine (Br) from substances and groups of substances controlled and not controlled under the Montreal Protocol have changed since the previous Assessment. The observed declines in total tropospheric Cl and Br from controlled substances during the 5-year period 2008–2012 were 13.4 ± 0.9 parts per trillion (ppt) yr<sup>-1</sup> and 0.14 ± 0.02 ppt yr<sup>-1</sup>, respectively.<sup>1</sup> [...]

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.265
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2014
Admission routes1
Has abstractyes

Explore more

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