Climatic signal in annual growth variation of Norway spruce (<i>Picea abies</i>) along a transect from central Finland to the Arctic timberline
Bibliographic record
Abstract
Regional and temporal growth patterns of Norway spruce (Picea abies (L.) Karst.) were evaluated in 40 stands along a transect of over 500 km running from central Finland to the Arctic spruce timberline. Standard deviation of the ring-width series increased from south to north, but the geographical differences in mean sensitivity and first-order autocorrelation were small. The high degree of similarity in growth variation between stands indicated similar growth responses of trees to weather variation despite different environmental conditions along the transect. The most pronounced differences in the regional increment chronologies were found between the southernmost and northernmost stands. Growth variation was most strongly correlated with current June mean temperature, and correlation between growth and July temperature increased from south to north. In addition, negative correlation was observed between winter temperatures, particularly February temperature, and growth variation. Growth was more weakly correlated with precipitation than with temperature.
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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 | 0.000 | 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".