Gišogenetic Variation in White-Spruce (Picea glauca (Moench) Voss) Trees of Yukon Beringia, Canada
Bibliographic record
Abstract
Gišogenesis, otherwise known as secondary-xylem development, was investigated in an old-growth upland population of white spruce (Picea glauca (Moench) Voss) trees having morphologically diverse crowns and growing on a south slope north of East Fork Creek bordering never-glaciated Yukon Beringia. After tree felling, trunks were segmented into one-metre lengths. In the laboratory, widths of xylem layers were measured across the four cardinal directions at each height, followed by Pearson’s product momentum correlations to evaluate variation in historical gišogenetic vigour within and between trees. Substantial variation was found, and it cannot readily be explained in terms of differences in extrinsic environment. Physiological differences in intrinsic gišogenetic regulation within a genetically diverse population, comprising both refugia and recent recruits, is proposed as a probable explanation, thus emphasizing the individuality of each tree’s internal control over how it responds to the extrinsic environment. Further investigations within Yukon Beringia may yield insight into evolutionary diversification of gišogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".