A Quantitative Definition of Light Rings in Black Spruce ( <i>Picea mariana</i> ) at the Arctic Treeline in Northern Québec, Canada
Bibliographic record
Abstract
Light rings in black spruce (Picea mariana [Mill.] BSP.) at the arctic treeline are characterized by pale-colored latewood made of a single or very few latewood-cell layers with thin-walled cells. Their widespread occurrence and their high frequency greatly facilitate the cross-dating procedure in dendrochronological studies. In this study, black spruce tree-ring density and wood structure were analyzed for light ring characteristics along with the mechanism of their formation according to ambient temperature. Light rings were quantitatively categorized into three classes based on the maximum tree-ring density using a normalized standard distribution. A light-ring chronology was established according to this classification. The results indicate that the grade of light ring was positively related to the frequency of light rings obtained from visual light-ring chronologies. The following anatomic variables were examined: number of cell layers of latewood, number of cells of the whole ring, percentage of latewood in the total ring width, and mean latewood cell-wall thickness. Among these anatomic variables, the mean latewood cell-wall thickness represents the best quantitative descriptor of a typical light ring as recognized by optical examination. The main causal factors of light rings are insufficient length of the growing season or cool summers.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".