Biochar greatly enhances methane oxidation in urban green roof substrate
Bibliographic record
Abstract
Filename: merged_sedum.csv: This dataset contains long-term field measurements of greenhouse gas (GHG) fluxes from extensive Sedum green roof modules located at the University of Toronto, collected between 2020 and 2024. The experiment investigated the effects of biochar amendment (20 t ha⁻¹; ~5% v/v) on methane (CH₄), carbon dioxide (CO₂), and water vapor (H₂O) fluxes, as well as associated substrate properties. Data were collected using static chambers connected to a LGR (Los Gatos Research) cavity ring-down spectrometer, representing one of the first multi-year assessments of CH₄ fluxes from urban green roof systems. Filename: sedum_flux_2020_2024:This dataset includes multi-year measurements of methane (CH₄), carbon dioxide (CO₂), and water vapor (H₂O) fluxes from Sedum green roof modules in Toronto, Canada, collected between 2020 and 2024. The experiment quantified seasonal greenhouse gas (GHG) dynamics under different substrate treatments, including biochar-amended and organic control plots. Fluxes were measured with static chambers connected to a Picarro G2508 cavity ring-down spectrometer, following standard GHG chamber protocols.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.012 |
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 source (direct Gemma or distilled Codex), 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".