DATA from: Jack pine of all trades: deciphering intraspecific variability of a key adaptive trait at the rear edge of a widespread fire-embracing North American conifer
Bibliographic record
Abstract
Data from: Jack pine of all trades: deciphering intraspecific variability of a key adaptive trait at the rear edge of a widespread fire-embracer North American conifer. American Journal of Botany. A MSExcel spreadsheet reporting results of 1) an experiment whereby closed jack pine (Pinus banksiana) cones were submitted to incrementing temperatures, and 2) a seed germination tests in order to investigate if and how various ecological factors (cone age, branch height, tree size, tree age) are related to cone dehiscence and seed viability in jack pines from the rear-edge (n = 17 sites) and the core (n = 7 sites) of the species’ range in eastern Canada. <br> <br> Sheet 1 - Metadata. Provides details about the study sites (Region, Site abbreviation, Site name, Sampling date, Longitude, Latitude, Altitude) <br> Sheet 2 - Stand-scale serotiny. At each site, up to 100 mature jack pine individuals were assigned to to one of six serotiny levels: class 0 (0% closed cones), class 1 (1−25% closed cones), class 2 (26−50% closed cones), class 3 (51−75% closed cones), class 4 (76−99% closed cones), or class 5 (100% closed cones). The diameter at breast height (DBH) of each tree sampled for serotiny is also provided in this sheet. <br> Sheet 3 - Experiments. At each site, 10 randomly-chosen mature jack pines were sampled. Three cone-bearing branches from different measured heights (lower, middle, and upper parts of the tree crown) were cut. For each tree, diameter at breast heigth (Tree DBH) was recorded and a core was sampled using a Pressler increment borer as close to the ground as possible. At the laboratory, three fully closed cones of contrasted ages were sampled from each branch (n = 1381 cones). Cone age and tree age was determined by counting growth rings. The cone opening temperatures correspond to the temperature required to reach each opening level, which refers to the relative abundance of opened scales on each individual cone (level 1: 1-25% opening, level 2: 26-50% opening, level 3: 51-75% opening and level 4: 76-100% opening). For each cone, the total number of seeds and the number of filled seeds were recorded. The filled seeds of each cone were batch-weighed. A total of 23,404 seeds were set to germinate. Every day (n = 33 days), germinated seeds (radicle > 2 mm) were counted.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.054 | 0.002 |
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; both teacher heads agree on what is shown here.
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".