Storm pulses of dissolved CO<sub>2</sub> in a forested headwater Amazonian stream explored using hydrograph separation
Bibliographic record
Abstract
Dissolved CO 2 dynamics in stormflow and event water versus preevent water contributions to storm hydrographs were assessed in a forested headwater catchment of the Brazilian Amazon using high‐frequency data. We applied the transfer function hydrograph separation model (TRANSEP) using specific conductance as a conservative tracer, finding preevent water to average 0.79 ± 0.03 of storm discharge (mean ± 1 SE for n = 14 storms). In situ, direct measurements of dissolved CO 2 were able to capture new hydrobiogeochemical processes in real time, including CO 2 pulses observed on the falling limb of storm hydrographs, the magnitudes of which were inversely related to preevent water fractions ( r = −0.97, p < 0.0001).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".