Bibliographic record
Abstract
At all locations the TGM measurements were made using automatic Tekran ® 2537 mercury vapour analyzers (described in detail in Poissant, 1997). The air is typically sampled at flow rates between 1.0 and 1.5 L/min (depending on location) and is passed through a Teflon filter (47 mm diameter; 0.45 µm) at the sample line inlet to remove particulate matter. Inside the analyzer, the mercury in the sample air is pre-concentrated before analysis by amalgamation on gold cartridges (5-30 minute concentration time). Mercury is removed from the gold cartridges by thermal desorption and is detected using Cold Vapour Atomic Fluorescence Spectrophotometry (CVAFS). The analyzer has two gold cartridges which allow alternating accumulation and desorption to occur simultaneously resulting in the continuous measurement of mercury in the air stream at 5-30 minute intervals. The instruments are calibrated daily using an internal mercury source and verified during routine site audits by manual injections of mercury from an external source. The data are quality controlled using the Environment Canada RDMQ (Research Data Management and Quality Control) system.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.022 |
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".