Bibliographic record
Abstract
Abstract In the summer of 1988, the ozone was in the wrong place. There was too much of it in American cities and not enough over Antarctica. Unusual weather, in combination with auto and other emissions, had led to the highest ozone concentrations in ten years in many cities. The American public raised a hue and cry for tougher clean air regulations, many of which had been relaxed in the past decade. Fortunately, the 1970 Clean Air Act and its subsequent amendments have produced the desired effects: emissions of some toxic gases have dropped more than 90 percent. Despite the fact that the United States leads the world carbon dioxide emission, recent improvements have disproved the notion that the American public is lethargic on certain environmental matters. Indeed, in both the matter of ozone in urban air and the ozone hole in the stratosphere, the public led its leaders. About 97 percent of all of the ozone in the atmosphere is found in the upper reaches of the stratosphere, where it absorbs otherwise dangerous ultraviolet radiation from the Sun, thus providing an effective blanket for life. The ozone layer presumably has existed throughout much of geologic time, and the Earth’s flora and fauna, including the human species, have evolved without having to contend with extreme doses of ultraviolet radiation. A marked thinning of the layer would cause, at the least, a corresponding increase in skin cancers, along with adverse effects on other forms of life.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.010 |
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".