Bibliographic record
Abstract
The monitoring of ambient environmental conditions is essential to environmental management and regulation.However, effective monitoring is subject to a range of institutional, political, and legal constraints, constraints that are a product of the need for monitoring to be continuous, long lived, and well matched to the resources being studied.Political pressure or myopia, conflicting agency goals, the need for institutional autonomy, or a reluctance of agency scientists to pursue monitoring all may make it difficult for ambient monitoring to be effectively undertaken.Even if effective monitoring data is gathered, it may not be used in decision making.The inevitable residual uncertainty in monitoring data allows stakeholders to contest the use of monitoring in decision making.Structural solutions, e.g., the creation of agencies to conduct monitoring separate from management or regulation and prompt use of that data in decision making, may be the most promising solutions.
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 | 0.106 | 0.270 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.020 | 0.035 |
| Open science | 0.009 | 0.013 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".