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 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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".