Evaluating the models of stomatal conductance response to humidity in a tropical rain forest of Xishuangbanna, southwest China
Bibliographic record
Abstract
The ecosystem-level fluxes of water vapour and carbon dioxide were measured from 2003 to 2006 at a tropical rain forest in Xishuangbanna, southwest China, using the eddy covariance (EC) technique. These flux measurements allowed the canopy-level evaluation of stomatal conductance (g) response to humidity models. The results showed that both the BWB model and the Leuning model discussed here underestimated g at high humidity and overestimated g at the mid-to-low range of humidity. In contrast, the Wang models discussed here (model-ha and model-Da) perfectly described the relationship of g response to humidity. The model comparison results also demonstrated high consistency over all the observation years. The good performance of the Wang model-ha and model-Da indicated that stomatal conductance responds more sensitively to humidity deficit or water vapour pressure deficit than to relative humidity itself at canopy level.
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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) | 0.000 | 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 | 0.001 | 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 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".