Bibliographic record
Abstract
For this afternoon field experiment, held on Monday September 22, 2014, data was collected throughout the York University Keele Campus’s woodlot from approximately 2:40PM - 5:15PM. The actual weather forecast (courtesy of http://www.accuweather.com/en/ca/toronto/m5g/september-weather/55488) for that time of day varied anywhere from as low as 7ᵒC to as high as 15ᵒC. With the use of transects tapes in the designated woodlot, the diameter (already in cm) of ten pairs of selected adult trees (White Oak) of the same species were measured at random from the centre of the adult trunk to its sapling (in meters and converted into centimeters) surface. Important to note was that the saplings were defined as trees that were no higher than relatively twice the height of an average student. As opposed to the grassland, the observable woodlot has an abundance and variation of not only living plant species, but also animals (insects, ladybugs, etc.) apparent in close proximity to each other. The execution component of the study was led by Taylor Noble in conjunction with a group of four males, one of which included myself. All four team members worked collectively as a unit to ensure the most accurate measurements pertaining to the Diameter at Breast Height (DBH), in addition to the distance of its nearest sapling for each and every one of the ten adult White Oak trees scattered across the woodlot. As for the overall determination to the extent of canopy coverage as a percentage, I, myself exclusively took on the responsibility of this rough estimate to avoid any biased judgment(s). To make the data collection valid and convenient, we as a whole chose a tree species that is large, close to saplings, and fairly distinguishable from the diverse categories of tree types evident. For these reasons as well as due to the random dispersal of this tree type throughout the area, we as a group came to the conclusion of randomly studying ten pairs of adult White Oak trees (one adult for every sapling observed) that were a resemblance to one another.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.079 |
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".