Dataset on soil carbon dioxide fluxes from an incubation with tropical peat from three different land-uses in Jambi Sumatra Indonesia
Bibliographic record
Abstract
Conversion of tropical peat swamp forests to increase and agricultural production has generated substantial peat carbon loss in the Asia-Pacific region. Different land-uses and management practices oxidize the tropical peat at diverse rates due mainly to different water table levels. In recent years, several studies have measured soil carbon dioxide emissions in-situ; however, only few studies have evaluated the effect of moisture on carbon dioxide fluxes in incubation experiments. Here, we present the dataset of an incubation performed with 360 intact peat cores from three different land-uses (i.e. 120 from intact peat swamp forest; 120 from drained logged peat forest; and 120 from oil palm plantation) collected on the peat dome of Jambi Sumatra Indonesia. Different moisture levels in the intact cores were set by either drying the intact peat cores for short period of time or by adding extra water before the incubation. Dynamic dark aerobic incubation in airtight containers coupled with carbon dioxide measurement with an infrared gas analyser and the gas fluxes was used to measure to gas fluxes. The average carbon dioxide fluxes were 5.38 ± 0.91, 4.15 ± 0.35 and 1.55 ± 0.13 µg CO2-C g−1 h−1 for the intact peat swamp forest, drained logged peat forest and oil palm plantation, respectively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".