Bibliographic record
Abstract
The 2017 ACS Summer School on Green Chemistry & Sustainable Energy took place at the Colorado School of Mines on June 20–27. The annual program, supported and financed by ACS, the ACS Green Chemistry Institute, and the ACS Petroleum Research Fund, is open to graduate students and postdoctoral scholars from institutions in the Americas. This year’s class of 53 students represented institutions in Argentina, Brazil, Canada, Colombia, Mexico, the U.S., and Uruguay. The schedule began with a barbecue and concluded with a banquet. Instructors from institutions in Canada and the U.S. gave presentations on the principles and practice of green chemistry, including information on biomass, fossil fuels, fuel cells, green chemistry education, ionic liquids, nanotechnology, research, solvents, synthesis, and toxicology. Additionally, instructors gave presentations on careers, entrepreneurship, research grant proposal writing, and ACS resources for graduate students and postdoctoral scholars. Students learned about each other’s research and mingled during poster
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 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".