Lab 2 - BIOL 2050 - Field training with plants.csv
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 study was conducted on September 21, 2016 in a woodlot at York University, Keele Campus, Toronto, ON, Canada by Pham Ha Phuong Do and Victor Suay Espi.<br>For data set #3, a random tree was selected, and 10 pairs of tree were randomly picked from the chosen tree. The distance between the trees in each pair was measured in meter by big measuring tape, and the diameters of each tree picked to pair with the chosen tree was measured in centimeter by a smaller pocket measuring tape. <br>To measure the distance between the trees, the measuring tape was used straight from the edge of the one tree to another. <br>The diameter of the trees was measured at approximately chest height of the main trunks.<br>*Note: Data set #4 and meta data are included in the same sheet, as cvs file doesn't allow multiple sheets in one file.
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) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.297 | 0.006 |
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