Lab 4 Data - Quadrats and Bait Traps near Danby Woods
Bibliographic record
Abstract
This data was collected on two different days, on October 13, 2013 and October 20, 2013, from 2:30 pm to 5:30 pm. The location was the grasslands (Oct. 13) and the woodlots (Oct. 20) in and around Danby Woods, in the York University Campus. On October 13, 2013, the weather was 16°C, and using the Beaufort Scale, the wind was determined to be mildly windy through the experiment. (Source: http://www.accuweather.com/en/ca/toronto/m5g/october-weather/55488?monyr=10/1/2014) On October 20, 2013, the weather was a cooler 12°C, and using the Beaufort Scale, the wind was determined to be mildly windy, growing windier as the experiment progressed. (Source: http://www.accuweather.com/en/ca/toronto/m5g/october-weather/55488?monyr=10/1/2014) For the grasslands (Oct. 13), quadrats were set up in low, medium and high disturbance areas, and data was recorded for high, medium and low disturbance areas. Each disturbance level had 10 quadrats repeated.Each quadrat was analyzed for roughly 3-4 minutes. Data regarding the area in the quadrat, such as grass length was recorded, along with the different animals that were captured. Bait traps containing sugar and cookies on a piece of paper towel were also set up in low, medium and high disturbance areas of the grasslands on the same day, and were left for about 1.5 hours. Each level of disturbance had 3 bait traps set up.The different animals that were in the bait trap were recorded. Next week, on October 20th, quadrats and bait traps were set up in the woodlot in Danby Woods. Similar to the previous setup, areas of low, medium, and high disturbance were selected and data was recorded after analyzing the quadrat for 3-4 minutes. Each level of disturbance had 10 quadrats repeated in different locations. The data comprised of the insects found in the quadrat. On the same day, bait traps containing sugar on a piece of paper towel were set up in low, medium and high disturbance areas. Each bait tra was left for 1.5 hours, and each level of disturbance had 3 different bait traps set up. The different animals that were caught in the bait trap was recorded.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.107 | 0.033 |
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".