A Study on the Relative Distance Between Adult Trees and Their Diameter at Breast Height.
Bibliographic record
Abstract
Metadata: Distance to Next Tree: To measure the distance between adult tees (in metres), a transect measuring tape was used and the center of one tree trunk was measured to the center of another tree’s tree trunk. (Numerical variable) The distances between trees varied from 2.1 to 7.2m.Diameter at Breast Height: A measuring tape was used and the diameter was measured against the tree trunk at approximately my chest height around 158 cm. (Numerical Variable) The diameters of the trees at breast height varied from 0.13m to 0.42m. Condition of Tree: This was determined based on a scale; 0=dead, 1=living, and 2=huge green canopy. (Response variable, Categorical)Methods: A 30m transect measuring tape was used to measure the distance (in metres) between two adult trees that were encountered and the data was recorded onto a table. Adult trees were selected if they lied on a straight line from the edge of the forest towards the centre. To meet the conditions of an adult tree, the tree had to be at least 0.1m in diameter and at least double my height (188cm). Furthermore, to measure the diameter of the trees at breast height, each tree was measured at approximately my chest height of 158cm using a measuring tape. To measure the distance between each tree, we measured from the centre of the first tree to the centre of the next tree. The condition of the tree was determined by the lab group’s observations; each person in the group determined what condition the tree was in on a scale of 0-2. 0 represented the tree being dead and 2 meant the tree was healthy with a lush green canopy. In total, 10 trees were observed to compile the data from this woodlot. Study Site Description: A field study was conducted at the Danby Woodlot located on York University’s campus near Keele Street and York Boulevard in Toronto, Ontario on September 22nd 2016, around 2:30 pm. The temperature was around 27 degrees Celsius, with sun and cloud, and a few hours into the study, a few raindrops began to fall. The woodlot was covered with lots of broken branches, leaves, soil, and was shady because of the large canopy trees. Hypothesis: The distance between the adult trees and the diameter at breast height will both have an effect on the tree’s growth conditions. The greater the distance between the trees, lack of competition results in greater nutrition and resources such as sunlight and space. Trees that are able to grow big, that have big trunks and have a large lush green canopy will be able to better, capture sunlight and resources compared to smaller trees. Prediction 1: The greater the diameter of the tree at breast height, the worse the condition will be of the nearby tree. Prediction 2: Trees that are farther apart from another will have healthier growing conditions. Prediction 3: The thicker the trunk of the tree, the tree will be healthier (example: lush canopy). Group Members: Keerthana Balachandran, Matthew Chiang, Andrew Nguyen, and Kobina Vijayakumar
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".