Plant height related to closesness of source of water, number of flowers, and umber of pollinators associated with the plant
Bibliographic record
Abstract
On October 14, 2014 at approximately 2:45 p.m, three 25m transects will be laid from the edge of Stong Pond out towards the grassland east of Stong Pond at York University. Each transect will have six quadrats placed on it with a 3 metre gap between the neighbouring edges of each quadrat. In the centre of each quadrat, a pan trap will be set to measure the number of insect pollinators in each quadrat. In total, there will be 3 transects, 18 pan traps, and 18 quadrats. To see if water affects the plant height, the distance from the centre of each quadrat to the closest edge of Stong pond will be measured and recorded using the transect that the quadrat is on. Data on the plant Canadian Goldenrod (Solidago canadensis) including: the number of S. canadensis, the total number of flowers, and the average height of the S. canadensis found exclusive to each quadrat will be measured and recorded. The number of flowers will be counted to see if any correlation between number of flowers and number of insect pollinators exist. The pan trap found in the centre of each quadrat will be used to record the number of insect pollinators caught which will be recorded 24 hours after setting the pan trap. This will conclude the experiment for week 1. On week 2, day of October 21, 2014 at approximately 2:45 p.m, the experiment conducted on week 1 will be replicated. The number of insects caught in the pan trap will be again recorded 24 hours after setting it.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".