Bibliographic record
Abstract
Letters to the editor Plastic wrap I would like to thank C&EN for its coverage of the growing problem of ocean plastic waste and single-use plastic items, such as packaging, covered in your June 18 issue (page 24). It is somewhat ironic, however, that my weekly C&EN is delivered in a single-use plastic wrap! Shaun D. Abbott Laval, Quebec Editor’s note: C&EN is delivered in a plastic wrapping in two instances: to prevent damage to the issue when delivered to international readers and to package the issue with an additional publication (for example, the “ACS Meeting Insider” delivered with the July 30 issue). In response to reader feedback, we commit to reexamining our C&EN delivery practices involving single-use plastics. July 30, page 36: The Global Top 50 feature incorrectly characterized the combination of Linde and Praxair. It is a merger of equals, not an acquisition of Praxair by Linde. In
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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.204 | 0.107 |
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".