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Record W4394447318 · doi:10.6084/m9.figshare.1232198

Human disturbance on insect diversity, abundance and plant diversity

2014· dataset· en· W4394447318 on OpenAlexaboutno aff
Maham Anees

Bibliographic record

VenueFigshare · 2014
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsDisturbance (geology)Abundance (ecology)Diversity (politics)EcologyPlant diversityInsectSpecies diversityGeographyBiodiversityBiologySociologyPaleontology

Abstract

fetched live from OpenAlex

The study that was conducted in this experiment is the human effect on insect diversity, insect abundance and plant diversity. Three sampling areas were selected based on the total vegetation coverage. The experimental areas were as follows: highly disturbed area intermediate disturbed area and last but not least, less disturbed area. The hypothesis of this study is that the area with moderate disturbance would contain the maximum species diversity. This prediction goes under the ecological theory of intermediate disturbance hypothesis. Furthermore at low level of disturbance, it is predicted to observe maximum abundance. Highly disturbed sampling area was selected near Vanier College. Two 20m transects were laid on the ground horizontally and vertically perpendicular to each other to measure 400 m2 sampling size. A numbered grid system was used to divide the 20m by 20m sampling area which was randomly selected into 25 grids using a random number table. Grids were numbered from 1 to 400, representing 1mx1m plots. Each experimenter then used the sweep nets of 35 centimeter (cm) diameter to catch the insects. The sweep nets were held about 10cm above the ground and moved back and forth from one edge to the opposite edge of quadrat. The sweeping motion was carried for about 1.5 seconds. The process was carried out similarly for the other randomly placed quadrats. Number of insect and different types of insects were observed and recorded in the data sheet. Based on visual observations of plant morphology or appearance, plant diversity was recorded. Plant diversity included grass and other different visible species of plant. The vegetation coverage was recorded based on visual observation by standing upright and making an estimate of the area covered by vegetation including grass. Vegetation coverage was recorded as a percentage value. The same process was done for Danby grassland which was sampled for intermediate disturbance level and for forest near the Pond road which was sampled for less disturbance level. The experiment was done on October 17, 2014 and October 24, 2014 from 2:30pm to 5:30pm in Keele campus of York University, Toronto Ontario. This experiment was done in groups of 3-4. Our group members included Sana Jamal, Ferinaz, Afraa Tarafdar and Maham Anees (me). The weather was cloudy. The temperature was approximately 16ᵒC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.123
GPT teacher head0.215
Teacher spread0.092 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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