Investigating the effects of Plant Diversity on the Total number of Insects collected and Rtus using a Transect and Sweeping Test
Bibliographic record
Abstract
<b>Meta Data:</b> Total Number of Insects Captured: This is a discrete variable. In the experiment, counted the total number of insects captured in the sweep test along a 30 m transect tape and 1 m perpendicular to the transect tape. Total number of Recognizable Taxonomic units (Rtus): This is a discrete variable. In the experiment conducted, among the insects captured in the sweep test were distinguished visually and obtained the number of Rtus by looking at the morphological features of the insect. For example; like small read fly, big black fly, cricket, beetle, spider, and bee. Plant Diversity: This is a discrete variable measured on an ordinal scale. Plant diversity was assessed through the scale of 0-3 where 0 = no plant diversity, 1= low plant diversity, 2 = medium plant diversity and 3= high plant diversity. Plant diversity was determined by the amount of different plant species found around the transect line. <b>Hypothesis:</b>It was hypothesized that increased amount of plant diversity and environmentally friendly conditions along the sweeping area will lead to increased amount of insects collected and increased number of Rtus. This is because if there is more plant diversity (i.e. more plants, more flowers, etc.) and sunlight along the sweeping area would attract more insects to that particular area leading to an increased number of collected insects and increased Rtus. <b>Predictions:</b>1. The more insects collected in a sweep will lead to increased amount of Rtus2. Increased plant diversity will result in more insects being collected within the transect. 3. Increased plant diversity will increase the amount of rtus within the transect. <b>Methods:</b>The experiment was conducted at the grass land at York university Keele campus at 2:40 p.m. E.T and lasted about 35 minutes. The transect was established by using the 30 m tape and aligning it in a linear fashion. The tape was set as low as possible without disturbing the area. Then the sweep test was conducted along the transect and started sweeping across approximately 1 meter perpendicular to each side of the transect for an overall distance of 30m. After thoroughly sweeping thoroughly through the grassland, started to count the total number of insects collected in the sweep net. After that, started to visually distinguish the insects into recognizable taxonomic units (rtus), for example like beetle, big black fly, small red eyed brown fly, spider, cricket etc. After that plant diversity was measured along the set up transect which was measured on scale of 0-3 (0 = no plant diversity (pd), 1= low pd, 2 = medium pdand 3= high pd). After that moved the 30 m transect horizontally approximately 3 m from the previous transect. The same process was repeated 9 more times with the same methods. <b>Study Site Description: </b>A field study was conducted at the Grassland located on York University’s Keele campus near Keele Street and York Boulevard in Toronto, Ontario on September 26 2016, around 2:40 pm. The temperature was around 18 degrees Celsius, gloomy skies, lots of cloud cover and periods of light rain . <b>Group Members:</b> Pedro Carrera, Arnab Shuvo
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| 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 | 0.000 |
| 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 teacher head, 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".