A 30-year dataset of CO2 in flowing freshwaters in the United States
Bibliographic record
Abstract
Abstract Increasing atmospheric carbon dioxide (CO 2 ) concentrations have been linked to effects in a wide range of ecosystems and organisms, with negative effects of elevated CO 2 documented for marine organisms. Less is known about the dynamics of CO 2 in freshwaters, but the potential exists for freshwater organisms to be challenged by elevated CO 2 . In flowing freshwaters CO 2 exhibits more variability than in lakes or the ocean, yet spatiotemporally extensive direct measures of CO 2 in freshwater are rare. However, CO 2 can be estimated from pH, temperature, and alkalinity—commonly collected water quality metrics. We used data from the National Water Quality Monitoring Council along with the program PHREEQC to estimate CO 2 in flowing freshwaters across 35,000 sites spanning the lower 48 US states from 1990 through 2020. Site data for water chemistry measurements were spatially joined with the National Hydrology Dataset. Our resulting dataset, CDFLOW, presents an opportunity for researchers to add CO 2 to their datasets for further investigation.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".