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Record W3019844162

The Effect of the Emerald Ash Borer

2020· article· en· W3019844162 on OpenAlexaboutno aff
Aidan Maddox, Abigail Ernat, Marco Bravo

Bibliographic record

VenueDigitalCommons-IMSA (Illinois Mathematics and Science Academy) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEmerald ash borerEnvironmental scienceForestryBiologyEcologyGeographyFraxinus
DOInot available

Abstract

fetched live from OpenAlex

Throughout both the United States and Canada, a single invasive species is wreaking havoc on the ecosystem. This species is a beetle known as the Emerald Ash Borer (EAB). In the midwest alone, millions of ash trees have already died, and in Canada studies showed that up to 99% of all ash trees were killed within 10 years of EAB infesting the first tree in an area. The Illinois government has tried to combat the insect by cutting down all trees as soon as they become infested, as well as by passing a law which requires people to have a permit in order to import and export firewood. However, this only slowed the spread of EAB, and in just 10 years it had spread throughout the country. To help gain awareness of the effect similar situations could have on our own IMSA students, we would plan to host a GA that talked about the importance of trees in an individual's everyday life. At this GA, we could bring up topics of what trees produce for us that we use in our everyday life, and how students can help combat the loss of trees themselves, possibly by attending a tree planting event. In addition, at these events we also plan to discuss how IMSA students can help to decrease the EAB population through environmentally friendly means.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2020
Admission routes1
Has abstractyes

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