Water State Study of Wood Structure of Four Hardwoods Below Fiber Saturation Point with Nuclear Magnetic Resonance
Bibliographic record
Abstract
Nuclear magnetic resonance (NMR) is a useful, powerful, and noninvasive technique to study the dynamics of wood-water relations, both quantitatively and qualitatively. The main objective of this study was to use NMR to characterize the state of water below the FSP. Two tropical hardwood species, huayruro (Robinia coccinea Aublet) and cachimbo (Cariniana domesticata [C. Martius] Miers), a plantation-grown eucalyptus species (Eucalyptus saligna Smith), and a temperate species, red oak (Quercus rubra L.), were studied. These species were chosen for their diversity in terms of anatomical and physical properties. Desorption tests were carried out at 21°C in a single-step procedure from full saturation state for huayruro, cachimbo, and red oak and from green condition for E. saligna. Discrete T2 times were obtained for each species and equilibrium moisture content (EMC). The results showed that even under EMC, there was a region in the hygroscopic range in which the loss of bound water takes place before all liquid water was drained. This region varies according to wood species. Furthermore, variation in the fast T2 values among the different wood species gives an indication of how bound water is distributed and arranged in sorption sites.
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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 | 0.001 | 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".