[Woodlot Dataset 4] Comparing the DBH of adult maples to nearby maple saplings
Bibliographic record
Abstract
The data was collected on Tuesday 23, 2014, at roughly 4:00 PM. The location was the Danby Woods at the York University Campus (Keele location.) At the time, it was 22°C (Source: http://www.theweathernetwork.com/monthly/canada/ontario/toronto) and it was a mildly windy day. To collect the required data, large, adult maple trees were located. The criteria for adult maple trees were that they must have a trunk circumference of at least 15 cm. Their circumference (at breast heigh) was measured using a tape measure (in cm, to a precision of 0.1cm) and recorded. The foliage coverage was also recorded by standing near the trunk of the tree, making a frame using our hands and estimating the amount of visible sky, and subtracting said number from 100 to determine foliage coverage. To maintain consistency, only I recorded the circumference at breast height. Next, maple saplings near the adult were located. The distance from the adult tree to the sapling was also recorded (in cm, to a precision of 0.1cm) The criteria for saplings were that they must have a circumfrence of less than 15cm. The circumference of the maple saplings were recorded (in cm.) Again, to maintain consistency, only I measured the saplings at my breast heigh. A total of 10 pairs (10 adult maples and 10 maple saplings) were collected, and the data was recorded. DBH was measured using the circumference collected during the experiment. The following equation was used: circumference = πd, where d refers to diameter. The collected circumference was divided by π to obtain the diameter of the trunk.
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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.048 |
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".