Estimating relative error in growth ring analyses of second-growth coast redwood (<i>Sequoia sempervirens</i>)
Bibliographic record
Abstract
Coast redwood (Sequoia sempervirens (D. Don) Endl.) grows in the coastal zone of north-central California and southern Oregon in pure and mixed-species forests. Redwood has long been recognized to exhibit unusual patterns within the annual growth rings typical of temperate forest trees, including partial and missing rings and ring-width anomalies. However, these patterns have not been quantified beyond a few suppressed trees. This study quantified the variation in ring counts occurring in 22 second-growth redwood trees from different canopy classes. Ring counts from cross sections taken at sample points along each tree bole revealed missing or incomplete rings in all sample trees and 70% of the cross sections. Ring counts along multiple radii were used to calculate probability of obtaining a maximum ring count along one radius. This probability was lowest at the tree base (0.25) and breast height (0.30) and highest near the top of the tree (0.90). Because of the high amount of variation present in ring counts at breast height, care should be taken when drawing conclusions regarding stand ages from increment cores. Increment cores should be taken from the longest axis of the tree and coring at tree base can be abandoned as cores are not likely to have higher ring counts than breast height cores.
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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 | 0.024 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".