Yield and composition of lipophylic extracts of yellow birch (Betula alleghaniensis Britton) as a function of wood age and aging under industrial conditions
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Bibliographic record
Abstract
Abstract The lipophylic extracts of yellow birch ( Betula alleghaniensis ) have been investigated to detect the effect of tree age and wood storage time on extract composition. A total of 17 wood disks were cut from trees belonging to different age groups at 1 m above ground and the wood was milled as usual for extraction (laboratory samples). In addition, 49 sawdust samples were collected in a lumber mill to study the effect of industrial processing on the extractives (industrial samples). All laboratory and industrial samples were extracted with dichloromethane under sonication. The chemical composition of the lipophilic extracts obtained was analyzed by GC-MS. A systematic (quasi-linear) relationship was found between the lipophilic extract yield and specimen age. A total of 30 constituents from yellow birch extracts have been identified, 26 of which have never been previously reported for B. alleghaniensis wood.
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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 | 0.000 | 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) | 0.000 | 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 it