A database of chlorophyll and water chemistry in freshwater lakes
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
Measures of chlorophyll represent the algal biomass in freshwater lakes that is often used by managers as a proxy for water quality and lake productivity. However, chlorophyll concentrations in lakes are dependent on many interacting factors, including nutrient inputs, mixing regime, lake depth, climate, and anthropogenic activities within the watershed. Therefore, integrating a broad scale dataset of lake physical, chemical, and biological characteristics can help elucidate the response of freshwater ecosystems to global change. We synthesized a database of measured chlorophyll a (chla) values, associated water chemistry variables, and lake morphometric characteristics for 11,959 freshwater lakes distributed across 72 countries. Data were collected based on a systematic review examining 3322 published manuscripts that measured lake chla, and we supplemented these data with online repositories such as The Knowledge Network for Biocomplexity, Dryad, and Pangaea. This publicly available database can be used to improve our understanding of how chlorophyll levels respond to global environmental change and provide baseline comparisons for environmental managers responsible for maintaining water quality in lakes.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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