New perspectives on radial profiles of specific gravity in North American conifers
Bibliographic record
Abstract
North American conifers exhibit three radial specific gravity (SG) patterns (Type 1, 2, and 3), which balance hydraulic and mechanical requirements. Type 1 and 2 patterns (Pinaceae) have low SG and high microfibril angle (MFA) corewood ensuring compliance, whereas in outerwood high SG/low MFA provide stiffness and strength resisting bending. Hydraulically, corewood, especially in Type 2 species, is resistant to embolism, whereas outerwood has higher specific conductivity. Cupressaceae (Type 3) have hydraulically very efficient, low SG outerwood, facilitating rapid growth. Corewood is flexible, whereas outerwood is mechanically weak and compensated for by more conical stems and durable heartwood (which prevents Brazier buckling). Radially earlywood (EW) decreases, and latewood (LW) increases for all types, whereas %latewood (%LW) increases (Type 1), decreases, then increases (Type 2) and decreases (Type 3). Ring SG increases when increasing LW SG and %LW are sufficient to counteract decreasing EW SG. Shade tolerance, crown recession, hormone gradients, and environmental variation affect patterns. Auxin concentration decreases with increasing distance from juvenile foliage slowing cell division, concomitantly gibberellin concentration (lignification) and carbohydrates (cell wall thickening) increase, producing higher %LW. Across a species range regions receiving relatively high summer rainfall have trees with higher %LW (by ring).
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".