Results of a bait trial testing predation in four vertical strata
Bibliographic record
Abstract
Data from a 2007 field study in the Morgan Arboretum, Ste-Anne-de-Bellevue, Québec. Associated with a published paper (https://peerj.com/articles/138/). This is a data file of 9 columns and 168 rows. Column information is as follows: Tree = tree identity, 21 mature sugar maples were used Stratum = vertical stratum of the branch used for the trial, including: UN - understory; LC = lower canopy; MC - mid canopy; UC - upper canopy Note that five mealworm baits were pinned to the branch in each stratum, and that baits were checked a total of four times over 150 minutes. The first observation was recorded after 60 minutes, and each successive observation was taken 30 minutes after the previous one. Baits were also checked after an overnight period. totpred = number of mealworm baits that were predated during the four observation periods notpred = number of mealworm baits not predated during the four observation periods t.1st = time (in number of observation periods) till first observed predation on a bait on that branch maxpred = maximum number of predators observed during one observation period on that branch p.rmvd = proportion of baits removed after overnight period rmvd = number of baits removed after overnight period left = number of baits left after overnight period
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".