Spatial and long-term temporal assessment of Lake Ontario water clarity, nutrients, chlorophyll <i>a</i>, and zooplankton
Bibliographic record
Abstract
Secchi depth, total phosphorus, soluble reactive phosphorus, silica, chlorophyll a, and zooplankton (density, biomass, and average size) were sampled as part of a lake-wide, seasonal (spring, summer, and fall) assessment of Lake Ontario in 2003 to characterize the status of the lower aquatic food web. For each parameter, spatial comparisons were performed to test for differences between habitats (nearshore and offshore) and between regions (east and west) during each season. Significant differences between habitats were found only for silica and chlorophyll a; silica was higher nearshore in fall, and chlorophyll a was higher offshore in fall. Significant differences between regions were detected in Secchi depth, epilimnetic zooplankton mean length, total phosphorus and Cercopagis pengoi density and biomass; Secchi depth and zooplankton mean length were higher in the east in spring, total phosphorus and Cercopagis pengoi biomass were higher in the west in summer, and Cercopagis pengoi biomass was higher in the east in fall. Cercopagis pengoi was present lake-wide in summer and fall, but Bythotrephes longimanus was present only in fall in the Kingston basin. Mean spring total phosphorus, soluble reactive phosphorus, chlorophyll a, and epilimnetic zooplankton density and biomass are at or near record low levels. As we move into the future, persistent low levels of these lower food web elements will continue to stress alewife populations both through reduced food resources and food quality for zooplankton, and may force these fish to seek alternative food such as Mysis.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".