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Ecology Lab 2 Grassland Dataset (Pond distance vs vegetation percentage)

2016· dataset· en· W6977252460 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2016
Typedataset
Languageen
FieldEngineering
TopicFluid dynamics and aerodynamics studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuadratGrasslandVegetation (pathology)ForbThistlePlant community

Abstract

fetched live from OpenAlex

This ecological experiment which was done at York University grasslands, Monday, September 20/2016, at 2:30 P.M, Studies the relationship between the vegetation percentage (ratio of plant individuals to grass) and the distance from the pond. The study was done using a 1meterx1meter square quadrat which was randomly thrown 25 times. <b>Methods</b> A 1meterx1meter square quadrat was used for this experiment. The quadrat was randomly thrown 25 times (n=25 trials) in the grasslands beside the pond and the total number of plant individuals, number of plant species, vegetation percentage, and grass percentage in the quadrat box were counted, calculated and recorded on a piece of paper. The data was then transformed into an excel sheet and uploaded on “FIgshare.com”. <b>Hypothesis</b> There is a correlation between the distance the individuals are from the pond and the percentage vegetation (vegetation density).<br> <b>Prediction</b> The quadrats that were randomly thrown closer to the pond will have a higher vegetation percentage than the ones thrown further away from the pond.<br> <b>Meta-data</b><b> </b> Trial number: the number of trials that the quadrat was randomly thrown to collect the data which was 25 times therefore n=25 trials. Canadian Goldenrod (yellow) Heath Ester (white), Butter and Eggs, Common Thistle (thorn), Late Purple Aster, small tree: Plants species found in York Universities grassland fields. Please refer to a plant atlas for more information about these plant species. Number of plant species: The different types of plant species that were seen in the quadrat box. Total number of plant individuals: The total number of plants in the square quadrat were counted. This included all species of plants in general and included any type of plant. i.e. how many plants in general in the box. Vegetation percentage (vegetation density): The percentage of plants compared to grass in the square quadrat. In other words, the ratio of plants to grass in the quadrat. Grass percentage (grass density): The percentage of grass compared to plants in the square quadrat. In other words, the ratio of grass to plants in the quadrat.

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 categoriesMeta-epidemiology (narrow), Insufficient 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.017
Threshold uncertainty score1.000

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)0.0220.004

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 head0.010
GPT teacher head0.224
Teacher spread0.215 · 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
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
Published2016
Admission routes1
Has abstractyes

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