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
The experiment was conducted in a woodlot located at the Keele campus of York University in Toronto, Ontario. It was conducted on the 15th and 22nd of October 2014 between 2:45pm and 4:30pm and the weather was cloudy with light precipitation. The only equipment required for the complete execution of the experiment was two 25m transect tapes and the chosen tree sample was a sugar maple tree (Acer Saccharum).First randomly place the 25m transect measuring tape from the edge of the woodlot (defined as the first tree you encounter as you enter the woodlot) to the centre, then at every instance we encounter an adult tree (defined as a tree twice the height of the students conducting the experiment) along the transect tape on both sides, various measurements were taken. First the distance on the transect tape where each sample maple tree was found was recorded then the dbh of the sample maple tree was also obtained using the second 25m transect tape. The distances from the maple tree to the three closest adult trees were obtained and recorded then the arithmetic mean of those distances was used to estimate the density of that specific maple tree. This was repeated for a total sample size of 30 transects.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.771 | 0.011 |
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