Prepared for: West Central Airshed Society
Bibliographic record
Abstract
Ambient air monitoring can be used to determine the status of air quality, and to understand deviations from natural background levels and changes over time (trends). Responding to public perceptions and concerns about air quality remains a challenge and requires sound assessment. It is of great interest to know whether changes in air quality have occurred over time in areas where economic development is on going and continuous air monitoring is conducted. Assessment of trends offers a sound scientific approach for responding to public perceptions and concerns about air quality and establishing whether or not change is occurring. The objective of this study was to examine the extent to which concentrations of ambient air quality parameters have changed (trends) over a period of 7 to 8 years at two West Central Airshed Society (WCAS) stations in central Alberta: i) Tomahawk (from 1997 to 2004) and ii) Carrot Creek (from 1998 to 2004). These stations are on the eastern side of the airshed within elevations 700 to 1000 m above sea level. While they are both located in predominantly rural areas, anthropogenic activities – oil and gas wells, gas processing plants, coal-fired power plants – occur in the area.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.340 | 0.097 |
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; the direct Gemma label and the distilled Codex classifier 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".