Accumulated wastewater calculations for smallmouth bass sampling sites in the Shenandoah River Watershed, USA
Bibliographic record
Abstract
This data release presents calculated accumulated wastewater (ACCWW, as a percent of total streamflow) values for 43 National Hydrologic Dataset Version 2.1 (NHDPlus V2.1) stream segments coinciding with long-term smallmouth bass sampling locations (Table 1) in the Shenandoah River Watershed (encompassing parts of Virginia and West Virginia, USA). Values are calculated for quarter-year (Quarter 1 [Q1], January - March; Quarter 2 [Q2], April - June; Quarter 3 [Q3], July-September; Quarter 4 [Q4], October-December) time scales (Table 2) and annual time scales (Table 3) for years 2000 to 2018. Estimates at a stream segment represent the combined total upstream wastewater discharges as well as direct discharges into the stream segment. Any users of these data should review the entire metadata record and the associated manuscript (see Larger Work Citation). See 'Distribution Liability' statements for more information.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".