Bibliographic record
Abstract
EARLY REPORTS of fourth-quarter earnings in the chemical industry suggest that demand for a wide variety of products has improved noticeably, giving executives reason to be optimistic about 2010. The year-over-year results are almost guaranteed to look good because the last quarter of 2008 was horrible for chemical firms. For example, DuPont earned $402 million for the quarter, compared with a loss of $249 million in 2008. In a conference call with analysts, DuPont CEO Ellen J. Kullman struck a triumphant note. “We delivered 10% sales growth in the quarter, with volume increases in every region,” she said. David Begleiter, a research analyst with Deutsche Bank, points out in a report to investors that DuPont’s earnings per share of 44 cents beat consensus expectations by 4 cents and observes that “the upside was driven by better-than-expected volume growth.” DuPont’s $6.4 billion in sales reflected growth in five of six segments, including a 22% increase in ...
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.071 | 0.012 |
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".