Cross-validation of the high-capacity tensiometer and thermocouple psychrometer for continuous monitoring of xylem water potential in saplings
Bibliographic record
Abstract
The pressure chamber, the most popular method used to measure xylem water potential, is a discontinuous and destructive technique and is therefore not suitable for automated monitoring. Continuous non-destructive monitoring could until very recently be achieved only by use of the thermocouple psychrometer (TP). Here we present the high-capacity tensiometer (HCT) as an alternative method for continuous non-destructive monitoring. This provided us with a unique chance to cross-validate the two instruments by installing them simultaneously on the same sapling stem. The HCT and the TP showed excellent agreement for xylem water potential less than -0.5 MPa. Response to day/night cycles and watering was remarkably in phase, indicating excellent response time of both instruments despite substantially different working principles. For xylem water potential greater than -0.5 MPa, the discrepancies sometimes observed between the HCT and TP were mainly attributed to the kaolin paste used to establish contact between the xylem and the HCT, which becomes hydraulically poorly conductive in this range of water potential once dried beyond its air-entry value and subsequently re-wetted. Notwithstanding this limitation, which can be overcome by selecting a clay paste with higher air-entry value, the HCT has been shown to represent a valid alternative to the TP.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".