Sample tree growth data with locations
Bibliographic record
Abstract
This file provides measurements of annual radial growth for randomly distributed adult trees in the Rocky Mountains of the United States. Measurements were derived from increment cores collected in 2012 and 2013. A total of 5 tree species were sampled. Sample trees were distributed across a latitudinal gradient from the southern terminus of the Rockies in New Mexico to the Canadian border in the north. Target tree species include: Abies lasiocarpa (subalpine fir), Picea engelmannii (Engelmann spruce), Pinus contorta (lodgepole pine), Pinus ponderosa (ponderosa pine) and Pseudotsuga menziesii (Douglas-fir). Annual radial increment over a 20 year period was measured in millimeters for each sample tree. File headings include:\n\nSample tree ID: Identification code for the sample or target tree\nSpecies: Species of the sample tree\nYear: The year of growth\nSite: General location of sample tree\nLongitude and Latitude: Geographical coordinates of sample (based on North American Datum 1983)\nElevation: Elevation above sea level in meters\nAspect: Dominant terrain aspect in degrees from north\nTerrain slope: Average slope of land surface measured in percent\nStem diameter: Diameter of tree stem at breast height (1.3 meters above root crown) in year of growth measured in centimeters\nAge: Age of sample in year of growth\nRing width: Measured width of annual radial increment in millimeters\nDate collected: Month, day, and year the sample was collected
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.217 | 0.146 |
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".