Bibliographic record
Abstract
As part of its annual salary survey, the American Chemical Society asked its members how they are faring during the COVID-19 pandemic. The results, collected between May 28 and July 15, 2020, show that members are more optimistic about the fate of the chemical enterprise than they are about the overall economy. But some ACS members are already feeling the impacts in the form of lower income and temporary or permanent layoffs. Part-time employees, postdocs, young scientists, and Black and Latino chemists are feeling the greatest effects. Most numbers are based on a survey conducted between May 28 and July 15, 2020, of 5,850 US ACS members. International responses to the same survey are presented for the 10 countries with the most responses, which were Brazil, 39; Canada, 107; France, 25; Germany, 39; India, 193; Italy, 29; Japan, 79; Nigeria, 29; Spain, 33; and the UK, 53. Some numbers have
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".