Sherbo et al. 2023 Data Package. Data associated with study assessing effects of dissolved organic matter on phytoplankton productivity in boreal lakes. The majority of data was collected in 2018 at the IISD Experimental Lakes Area in Northwestern Ontario
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
Allochthonous dissolved organic matter (DOM) structures many physical, chemical, and biological properties of lakes, including key variables that control productivity at the base of freshwater food webs. We examined phytoplankton biomass and productivity and their drivers, across eight pristine boreal lakes with DOM ranging from 3.5 to 9.5 mg DOC L-1. Increases in DOM were associated with significant increases in epilimnetic nitrogen, phosphorus and chlorophyll a (Chl a) concentrations suggesting that nutrients associated with DOM stimulate phytoplankton biomass and productivity. Such results were misleading; there was no significant relationship between Chl a and phytoplankton biomass measured via microscopy, and results did not incorporate the effects of DOM on thermocline and euphotic depth. Chl a:biomass and Chl a: carbon ratios indicated that increases in Chl a with DOM were driven by photo-acclimation to declining light availability. Increases. Further, increases in DOM led to large declines in thermocline (~50 %) and euphotic (~75 %) depths, and depth-integrated phytoplankton biomass and primary production (~70 %).
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.013 | 0.032 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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