Act as NARSTO Management Coordinator and Conduct Research In Support of NARSTO Activities
Bibliographic record
Abstract
This grant funded the position of NARSTO Management Coordinator. NARSTO was a public-private partnership with members from government, utilities, industry, and academe in Canada, the United States and Mexico. NARSTO planed and coordinated independently sponsored projects and tasks designed to identify and resolve policy-relevant science questions related to a) Anthropogenic and biogenic air-pollution sources and emissions, b) The complex physical and chemical processes affecting the accumulation of pollutants in the troposphere (including greenhouse gases and aerosols), c) The potential of certain pollutants to react and generate oxidants and fine particles in the troposphere, d) The development, intercomparison, and application of atmospheric models, e) The development of monitoring studies and methodologies needed to assess emission control effectiveness for selected greenhouse gases and aerosols, air pollutants and their precursors, and f) The attainment of the national air-quality and climate-stabilization goals and standards established by each member Nation.
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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.187 | 0.087 |
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".