Bibliographic record
Abstract
Irondequoit Bay is approximately 4.2 miles long and 0.6 miles wide and is separated from Lake Ontario by a small barrier beach. Irondequoit Bay had been historically considered hypereutrophic when several sewage plants discharged directly into the bay; however, aggressive restoration by Monroe County has improved the eutrophic state of the bay. Restoration efforts included sealing the bottom sediments with alum, reducing both point and non-point sources of phosphorus, and the pumping of air into the hypolimnion to reduce phosphorus movement from the sediments into the water. Currently no direct sewage plant discharge is received, and phosphorus levels are approaching goals set by the county. Irondequoit Bay is located within the Rochester embayment, an indentation of the shoreline stretching from Bogus Point to Nine Mile Point. Much of the southern shore of Lake Ontario, the Bay, and the shoreline of Lake Ontario experience nuisance algae, bacteria, and algal mat development which foul the nearshore waters and limit water recreation. This short report provides a synopsis of data collected monthly from May through September (2003 to 2009) on the water quality of Irondequoit Bay and the lakeside (swimmable depth) of Lake Ontario near the mouth of the bay.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.045 | 0.004 |
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".