Low moisture availability reduces the positive effect of increased soil temperature on biomass production of white birch ( <i>Betula papyrifera</i> ) seedlings in ambient and elevated carbon dioxide concentration
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Bibliographic record
Abstract
White birch ( Betula papyrifera Marsh.) seedlings were grown under two carbon dioxide concentrations ([CO 2 ]) (360 vs 720 μmol mol −1 ), three soil temperatures (T soil ) (5, 15, 25°C initially, increased to 7, 17, 27°C, respectively, one month later), and three moisture regimes (low: 30–40%, intermediate: 45–55%, high: 60–70% field water capacity) for four months in environment‐controlled greenhouses. The dry mass of stem, leaves, and roots was measured after 2 and 4 months of treatment. Low T soil decreased stem, leaf and total biomass in both measurements, however, the decrease was significantly greater in the elevated than ambient [CO 2 ] after 4 months. Intermediate T soil increased root biomass in both measurements. Low moisture reduced stem, leaf, root and total biomass after both 2 and 4 months of treatment. There was a significant T soil ‐moisture interactive effect on leaf, root, and total biomass after 4 months of treatment, suggesting that the magnitude of biomass enhancement in warmer T soil was dependent on the moisture regime. For instance, the increase in total biomass from the low to high T soil was 22, 50, and 47% under the low, intermediate and high moisture regimes, respectively. In contrast, the T soil ×moisture effect on stem biomass was significant after 2 months, but not after 4 months of treatment. High T soil increased leaf mass ratio (LMR) after 4 months of treatment, but decreased both root mass ratio (RMR) after both 2 and 4 months, and root:shoot ratio (RSR) after 4 months of treatment. The low moisture regime decreased LMR after 2 and 4 months of treatment, but increased RSR after 4 months of treatment. There were no significant [CO 2 ] effects on biomass allocation or [CO 2 ]×T soil ×moisture interactions on biomass production/allocation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it