YorkU.near.pond.impermeable.area.oct26-2016
Bibliographic record
Abstract
The study was conducted on October 26, 2016 in two locations: Pond (representing near pond habitat) and Baseball diamond (representing impermeable area) of York University (Keele Campus), Toronto, ON by Pham Ha Phuong Do, Victor Suay Espi, Achal Amin and XinLu (Andrew) Fan. The temperature was 5 degrees Celsius, very cloudy with medium wind. The weather was cold, causing difficulties in collecting data. 2 transects (30 meters length each) were used to create a long line, combined length of 50 meters. The survey was conducted along the 50m transect line. For data set #1 (Herbaceous plants) - conducted by Andrew Fan, a quadrat is placed randomly every 2 meters (repeat 25 times in total) along the transect. Native and exotic plants are identified and counted. The total number of observed flower heads within quadrat is also recorded.*Note: all random locations in data set #1 were determined by a random number generator, available at: https://www.random.org/ One number from 1 and 2 will be randomly selected by the generator, deciding the location of the quadrat: 1 is on the right side of the transect, 2 is on the left side. The same method is used to determine the direction of the quadart: 3 is parallel with the transect, 4 is not. For data set #2 (Woody plants) - conducted by Pham Ha Phuong Do, every 2 meters along the transect (repeat 25 times in total), any woody plant higher than 1.5 meters and within 0.5 meters on either side of the transect will be counted. At these points, canopy coverage is also estimated by dividing visual area into quadrats then sum the area covered. The same method is used to estimate vegetative ground cover as well as record the total number of flower. For data set #3 (Vertebrates & Invertebrates) - conducted by Achal Amin, data was collected for vertebrates by recording the total number of vertebrate individuals (including people who are not in lab group) in 50 meters radius from the beginning point of the transect. In another 15 minutes interval, the invertebrates data was collected by observing the amount of invertebrates present in a smaller area - 5 meters radius from the beginning point of the transect. For data set #4 (Invertebrates) - conducted by Victor Suay Espi, insects captured via 6 pan traps filled with soapy water placed 3 meters apart from each other alongside a transect while alternating colours (blue, white and yellow). The number of invertebrates found in the traps is recorded at the end of the session. In addition, 10 sweep nets next to the 50 meters transect were also conducted. Each sweep transect is one replicate, and the number of invertebrates is recorded after each sweep. Key to variables:- abundance.native.plants: total number of individual plants recorded inside quadrat in data set #1 that are native to Ontario.- abundance.exotic.plants: total number of individual plants recorded inside quadrat in data set #1 that come from places other than Ontario.- total.number.flowers (quadrat): total number of flowers inside quadrat recorded in data set #1.- abundance.woody.plants: total number of individual woody plants higher than 1.5 meters within 0.5 meters on either side of transect recorded in data set #2.- canopy.cover: percentage of sky view (looking up) covered by canopy recorded in data set #2.- ground.cover: percentage of ground covered by vegetation recorded in data set #2.- total.flower.numbers (transect): total number of flower heads within 0.5 meters on either side of transect recorded in data set #2.- abundance.vertebrates: total number of individual vertebrates observed within a 50 meters radius from location recorded in data set #3.- vertebrate.richness: the number of different vertebrate species recorded in data set #3.- abundance.human: total number of people that do not belong to our lab recorded in data set #3.- abundance.invertebrates.pantraps: total number of individual invertebrates caught by pan traps recorded in data set #4.- abundance.invertebrates.sweeps: total number of individual invertebrates caught by sweep net recorded in data set #4.- abundance.invertebrates.observed: total number of individual invertebrates caught within a 5 meter radius during 15 minutes interval recorded in data set #3/4. Hypothesis:Data set #1: The native plants and flower in pond is more than impermeable area because pond has full ecology niche which can positively affect the plant growth surrounding the pond. Data set #2: Impermeable area, which doesn't hold water and provide any nutrient, is totally unsuitable for any kind of vegetation to grow. Data set #3: Pond habitat has more biodiversity and species abundance of vertebrates and invertebrates comparing to impermeable habitat. Data set #4: The cold weather reduces the number of invertebrates moving around. PredictionsData set #1: The number of native plants and flowers in pond is more than impermeable area. Data set #2: There's no plant in impermeable area, ground cover is 0%. Data set #3: Impermeable habitat has no species richness or abundance of invertebrates. It has low abundance of vertebrates compared to the pond habitat. Data set #4: The total number of invertebrates caught by sweep net and pan traps is significantly lower comparing to the number in previous labs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.489 | 0.269 |
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".