Liquid water content of wood tissue at temperatures below 0°C
Bibliographic record
Abstract
Time domain reflectometry (TDR) offers an opportunity to measure the liquid water content of otherwise frozen plant material. We applied TDR technology to the examination of freezing in three types of wood represented by Robinia pseudoacacia L. (ring porous), Populus trichocarpa Torr. & A. Gray (diffuse porous), and Pinus contorta Dougl. ex Loud. and Larix occidentalis Nutt. (conifer wood). Gravimetric analysis revealed similar water contents of all wood types during the summer. In contrast, winter data showed that R. pseudoacacia wood exhibited a lower total (liquid and ice) water content (0.250 m3·m-3) than that of Populus trichocarpa (0.600 m3·m-3) or of the two conifer species' wood (0.510 m3·m-3). Additionally,R. pseudoacacia wood contained more air by volume during the winter than all other wood types (air-filled porosity 0.34 m3·m-3 compared with 0.12-0.22 for all other species). At all temperatures below 0°C, R. pseudoacacia wood contained less liquid water than the other wood types, as revealed by TDR measures. The TDR analysis further demonstrated that more than 25% of the water in wood of all species was liquid even at temperatures of -15°C. This liquid water is likely found within the cell wall and is potentially transportable at temperatures well below 0°C.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".