Modelling impacts of recent warming on seasonal carbon exchange in higher latitudes of North America
Bibliographic record
Abstract
An ecosystem model, ecosys, has been used to examine the effects of recent warming on carbon exchange in higher latitudes of North America. Model results indicated that gradual warming during the past 30 years has increased net ecosystem productivity (NEP) and leaf area index (LAI). Spring increases in LAI advanced by 2.3 days decade −1 and decreases in autumn were delayed by 5.0 days decade −1 from 1982 to 2006. These advances and delays were corroborated by similar trends observed in the normalized difference vegetation index. NEP modelled during this period increased at an average rate of 17.6 Tg C decade −1 . Increasing carbon losses modelled with soil warming in autumn, when thaw depth was greatest, offset 34% of increasing carbon gains modelled in spring. If autumn warming continues, carbon losses in this season may further offset enhanced carbon sequestration in spring.
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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 | 0.001 |
| 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) | 0.001 | 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 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".