Bibliographic record
Abstract
Figure: Over the years, we've sometimes opted to put a scenic beach on our August cover to evoke a sense of calm and tranquility, something we can all appreciate as school ends, flu and cold season grinds to a halt, and, if we're lucky, we embark on a much-needed vacation.Over the years, we've sometimes opted to put a scenic beach setting on our August cover to evoke a sense of calm and tranquility, something we can all appreciate as school ends, flu and cold season grinds to a halt, and, if we're lucky, we embark on a much-needed vacation. But this summer, as our staff poured over photos of beautiful beaches, we couldn't help but think of how summers are changing, with some areas of the country facing more extreme weather conditions and hotter temperatures. According to the Environmental Protection Agency, since 1901, the average surface temperature across the contiguous 48 states “has risen at an average rate of 0.17°F per decade,” with temperatures rising more quickly since the late 1970s. The most recent decade was the nation's warmest on record, and temperatures are expected to continue to rise. At the time of this writing, the Northeast has just cleared unprecedented hazardous smoke that brought the air quality alerts up to the highest levels in some states. The smoke descended from Canada, which is seeing its worst wildfire season in years, and is expected to continue to affect parts of the United States throughout the summer. Consequently, the photo chosen for this month's cover, of a wind power station by the sea in Zhoushan, China, seemed appropriate. With the wind turbines in the distance offering an alternative to fossil fuels, and a lone man on the beach evoking a sense of how small we are in the grand scheme of the world we live in, it is, as the photo site Shutterstock described, “a perfect combination of green energy and nature.”—Amy M. Collins, managing editor
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.947 | 0.872 |
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".