Chemical pretreatment of Thuja occidentalis tree rings: implications for dendroisotopic studies
Bibliographic record
Abstract
Whether or not extractives, lignin, and (or) hemicelluloses, all of which have specific isotopic signatures, should be removed prior to dendroisotopic analysis is still debated. This study reports the range of modern tree-ring δ13C values of cellulose from Thuja occidentalis L., a species that has been under-utilized in dendroisotopic research despite its broad distribution and great longevity in North America. The main objective of the study was to recommend a wood component from T. occidentalis to isolate for future δ13C dendroisotopic analyses. Annually resolved tree-ring decadal segments common to eight T. occidentalis trees were excised from cross sections and homogenized. The tree-ring decadal segment from each tree was then chemically processed from untreated whole wood to extractive-free wood, to holocellulose, and to α-cellulose. Subsamples were analyzed for δ13C, percent carbon, and percent yield after each stage of chemical treatment. We recommend that holocellulose be extracted for T. occidentalis, as the α-cellulose yield may be too low when tree-ring samples are very small. The δ13C values for T. occidentalis tree rings were found to be enriched with respect to those for needle-leaved conifers but in close agreement with those reported in the literature for other scale-leaved evergreens.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".