Salinization as a driver of eutrophication symptoms in an urban lake (Lake Wilcox, Ontario, Canada)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, we identified the mechanism(s) responsible for the intensification of eutrophication-like symptoms in Lake Wilcox, using statistical analysis (Principal Component Analysis (PCA) and Multiple Linear Regression (MLR)) of water chemistry timeseries. The dataset contains changes in nutrient concentrations in Lake Wilcox; changes in ratios between phosphorus (P) species and P and nitrogen (N) species; changes in the Brunt-Väisälä frequency (which represents the amount of work required against gravity to break down thermal stratification in the water column); and the results of the PCA and MLR statistical analyses. The methods used to derive this dataset and the interpretation of the dataset are reported in the paper "Salinization as a driver of eutrophication symptoms in an urban lake (Lake Wilcox, Ontario, Canada)" from authors Jovana Radosavljevic, Stephanie Slowinski, Mahyar Shafii, Zahra Akbarzadeh, Fereidoun Rezanezhad, Chris Parsons, William Withers, and Philippe Van Cappellen.
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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 it