A compilation of North American tree provenance trials and relevant historical climate data for seven species
Bibliographic record
Abstract
Tree provenance trials consist of a variety of seed sources (or provenances) planted at several test sites across the range of a species. The resulting plantations are typically measured periodically to investigate provenance performance in relation to abiotic conditions, particularly climate. These trials are expensive and time consuming to establish, but are an important resource for seed transfer systems, which aim to match planting sites with well-adapted (climatically suitable) seed sources. Provenance trial measurements may be underutilized because the data are scattered across publications, conference proceedings, and university theses. Here we document an effort to collect available provenance trial measurements and associated climate data for seven eastern North American tree species (Pinus strobus, Pinus banksiana, Picea glauca, Picea mariana, Quercus rubra, Larix laricina, Betula alleghaniensis). The resulting datasets included a total of 773 provenances and 62 test sites, with 65 historical climate variables appended to each location. We hope this data will support forest managers in making seed transfer decisions, particularly in an era of rapid climate change.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".