Data for: Gas Transfer Velocities Evaluated Using Carbon Dioxide as a Tracer Show High Streamflow to Be a Major Driver of Total CO2 Evasion Flux for a Headwater Stream
Bibliographic record
Abstract
This dataset contains direct in-situ measurements and modeled values of stream properties and air temperature of a steep, turbulent headwater stream in southwestern British Columbia, Canada, between November 2016 and June 2017. The dataset is associated with a study of CO2 evasion from experimental stream G-H in the University of British Columbia Malcolm Knapp Research Forest, which estimated gas transfer velocities of CO2 (kCO2) and CO2 evasion using an automated in situ CO2 tracer technique. McDowellJohnson2018_continuousdata.tab contains continuous half-hourly stream data for the duration of the study period. McDowellJohnson2018_injectiondata.tab contains averaged values of stream data associated with 38 one-hour injections of CO2. Continuous data variables: date-time, CO2 concentration, pH, water temperature, electrical conductivity, air temperature, stream discharge, stream depth, water velocity, modeled gas transfer velocity of CO2, modeled gas transfer velocity of CO2 normalized to a Schmidt number of 600, dissolved oxygen concentration Injection data variables: date-time, stream depth, gas transfer velocity of CO2, gas transfer velocity of CO2 normalized to a Schmidt number of 600, stream discharge, water temperature, water velocity This work was conducted on the unceded, ancestral territories of the xʷməθkʷəy̓əm (Musqueam) and Katzie peoples.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 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".