Field Training with Plants: A study on sampling populations and communities of a plant species in the grasslands
Bibliographic record
Abstract
Methods: By randomly placing transect tape within the grasslands of Danby Woods, 50 individuals of a targeted plant species were sampled at specific distances on the transect for number of flowers, number of leaves, height, and whether it was located in a crowded patch of other plant species. Study Site: Danby Woods, York University, ON, Canada. 43.7735° N, 79.5019° W. Study taken outdoors with a bit of rainfall and complete cloud cover. Hypothesis: There will be a correlation between plant height and surrounding density of other plant species because competition of nutrients between multiple plant species affects the ability of a single plant to grow and flourish. Predictions:1. The more crowded the target plant is by other plant species, the shorter it will be because as the nutrients are shared among many plants, the targeted plant species can only uptake a certain amount to sustain the plants life.2. The more crowded the target plant, the less number of leaves and flowers because it will be competing with other plants for nutrients which help produce more flowers and leaves.3. The targeted plant species will be taller, and produce more leaves and flowers in a less crowded area because they will not be competing for nutrients with many other plant species. Meta-data:1. distance (transect): Numerical and Discrete – Recorded distance traveled on a transect in meters to 50 targeted plant species which were sampled within a radius of 50 centimeters on each side of the transect to a maximum distance of 30 meters on the transect.2. height.of.plant.of.interest: Numerical and Continuous – Recorded plant height from ground level to tip of the tallest flower in centimeters using a measuring tape.3. total.number.of.leaves: Numerical and Continuous – On each plant, an average length stem was counted for number of leaves, and then that number was multiplied by the total number of stems on the whole plant itself to get the total number of leaves for each plant.4. total.number.of.flowers: Numerical and Continuous – Only counted purple flowers which were already bloomed and disregarded flower buds on targeted plant. 5. crowdness.around.plant.of.interest: Categorical and Ordinal – Assigned a ranking system of 0 (open), 1 (some plants nearby), 2 (quite a few plants), and 3 (very crowded bunch of plants) to signify the estimated density of the targeted plant’s environment within a 50 centimeter radius. Group Members: Matthew Fernandez, Rija Ghani, Niyousha Taati, Sarah Pecile
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".