Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This data set contains two files (.txt format). One file provides above- and below-ground biomass, soil, and nutrient data for a mature boreal ecosystem (subarctic Picea mariana/lichen woodland) near Schefferville, Canada (54.72 N, -67.70) for the 1974 growing season. The second data file contains climate data (precipitation amount and maximum/minimum temperature) from a weather station located 22 km northeast of the study site for the 1948-1990 period. The black spruce/lichen woodland is a vegetation type found in the transitional zone between boreal forest and tundra on well-drained, nutrient-poor podzolic soils. These spruce/lichen woodlands are generally not subject to attack by herbivory, but natural fires are common. The study forest was estimated to be 110 years old, based on annual tree ring data which showed the number of years since it was last burned. Biomass estimates were determined by harvesting trees, shrubs, and ground cover in the 0.2 ha study plot. To confirm the "typical" nature of the site, species composition and density were evaluated for the principal plot and compared to that of fifteen other plots. Organic and mineral soils were also extracted. The plant and soil samples were evaluated for nutrient and mineral content. Living tree, shrub, and lichen components contributed a total biomass of 2,636, 833, and 939 g/m2, respectively. NPP was estimated by the Terrestrial Ecosystem Model (TEM) to be about 340 g/m2/yr. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2001.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it