TECHNICAL PROGRESS IN ELIMINATING THE USE OF CHLOROFLUOROCARBONS IN THE POLYURE THANEINDUSTI
Bibliographic record
Abstract
Depletion of the stratospheric ozone layer now ranks near the top among global environ-mental problems. As a result of the attention focused on this issue, an unprecedented in-ternational agreement has been reached which mandates curtailment of the production and use of fully halogenated chlorofluorocarbons (CFCs). That Agreement, the Montreal Protocol on Substances that Deplete the Ozone Layer, was signed in September 1987 and was subsequently ratified by the majority of signatory nations. The phased reductions in CFC production and consumption required by the Protocol are now well known to most individuals in the industries which use CFCs. Beginning July 1, 1989 CFC production and consumption were frozen at 1986 levels; by mid-1993 and by mid-1998 CFC production and consumption must be reduced by 20 percent and another 30 percent, respectively, for a final reduction of 50 percent from 1986 levels. The Montreal Protocol accelerated what was already a major industry effort to find suitable alternatives for CFCs. Both CFC producers and end-user industries had been researching substitutes or alternative production and processing technologies to reduce CFC use. Although much research into substitutes remains to be done, tremendous strides have al-ready been made toward reducing CFC use in polyurethanes and polyisocyanurates. This
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".