Ecosystem-scale methane emissions from peatlands of the Hudson Bay Lowlands
Bibliographic record
Abstract
Daily average methane (CH4) fluxes and corresponding daily average values of environmental factors (calculated from gapfilled datasets) used to characterize drivers of methane fluxes at four peatland sites in the Hudson Bay Lowlands: 1) a treed patterned fen near Attawapiskat River (Ameriflux code: CA-ARF and abbreviation, ARF, 52⁰42'02'' N, 83⁰57'18'' W); 2) a bog near Attawapiskat River (Ameriflux code: CA-ARB and abbreviation, ARB, 52⁰41'42'' N, 83⁰56'42'' W); 3) a peat plateau with permafrost table at about 1 m depth in Polar Bear Provincial Park (Ameriflux code: CA-PB1 and abbreviation, PB1, 54⁰56'30'' N, 83⁰27'28'' W); 4) a thawing peatland in Polar Bear Provincial Park (Ameriflux code: CA-PB2 and abbreviation, PB1, 54⁰56'20'' N, 83⁰28'25'' W). Methane fluxes were measured with the eddy covariance technique. The second column (CH4 flux) contains all daily average CH4 fluxes calculated from gapfilled data, while the third column ("CH4 flux with >= 8") contains daily average CH4 fluxes calculated for days where at least 8 non-modelled 30-minute averages were available in the day. Total season (April 1 - Nov 30) gap-filled methane fluxes and gross primary productivity (GPP) derived for the four peatland sites described above. GPP was derived from eddy covariance flux measurements of net ecosystem CO2 exchange and gap-filled as described by Beaver, J., Humphreys, E. R., & King, D. (2024). Random forest development and modeling of gross primary productivity in the Hudson Bay lowlands. Canadian Journal of Remote Sensing/Journal Canadien de Teledetection, 50(1). https://doi.org/10.1080/07038992.2024.2355937
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".