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Effect of Crowding and Plant Height on Insect Abundance

2015· article· en· W2268294201 on OpenAlexaboutno aff
Michael Angelini, Kate Britanico, Kristine Del Rosario, Khan Nassar

Bibliographic record

VenueFigshare · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicInsects and Parasite Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAbundance (ecology)CrowdingInsectDistance samplingBiologyGeographyEcology

Abstract

fetched live from OpenAlex

This experiment was done at the grasslands at york university, Toronto Canada over the course of two days between the hours of 2:30 PM and 5:30 PM. On day one the weather was approximately 13 Degrees C and mostly sunny and day 2 was partly cloudy and approximately 10 Degrees C. In this experiment 40 plastic bowls (each day totaling 80 bowls), all of the same colour were placed randomly within the grasslands and filled at least one quarter the way full with soapy water. After all bowls were placed a 1m by 1m quadrat was placed around each bowl and the crowding of living or dead plant matter within the quadrat was estimated from 0-4 (0 meaning no plant biomass 4 meaning no ground could be seen through the plants). Afterwards, the average plant height was estimated with the use of a transect. The tallest and shortest plants were measured, the estimation was made based upon how much area the talest and shortest plants took up within the quadrat and the measurement was recorded in inches. after all measurements had been taken, the bowls were left for 2 hours. When the 2 hours were up the bowls were collected and the number of insects caught in the bowls were counted and recorded. This experiment was conducted to see how the abundance of insects were effected by plant height and plant crowding. This data can be useful to see which, crowding or height, effects insect abundance more. It is also interesting to note that even though the temperatures for both days of the experiment were close, only 3 degree difference, there were significantly fewer insects on the second day of testing.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0340.002

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.

Opus teacher head0.039
GPT teacher head0.273
Teacher spread0.234 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2015
Admission routes1
Has abstractyes

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