Bibliographic record
Abstract
This test was done at the grassland at York university, Toronto Canada. The test was done between the hours of 3:30 and 5:30. It was approximately 14 degrees celcius and sunny. The test included taking a sweep net and swinging it for exactly 1 minute in tall grass while walking a straight line guided by a transect laid out 5 meters. the transect was laid out in random spots in the grassland 10 times, once for each repitition. After each repitition of the experiment the net was held closed and the total amount of insects inside, as well as the recognizable taxinomic units of the insects, were counted and recorded. The purpose of this experiment is to see how many insects could be found on the first cold day of the fall season. In order for this dataset to be most useful one must compare this data with that of similar tests done on a warmer day, and colder day, and of similar variables (sunny, clear sky, between the hours of 3:30 and 5:30, same grassland, randomly selected spots) so the results can be compared.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.088 | 0.107 |
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".