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Dynamics of dispersal: Modeling the impact of dandelion proliferation on environmental and economic equilibria

2024· article· en· W4399984770 on OpenAlexaboutno aff
Leyi Jiang, Mingjun Ouyang, Weiyu Qi, Yueyue Yu

Bibliographic record

VenueTheoretical and Natural Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDandelionBiological dispersalCreaturesSeed dispersalPopulationDifferential (mechanical device)Fuzzy logicSensitivity (control systems)GeographyEcologyComputer scienceBiologyEngineeringArtificial intelligenceSociology

Abstract

fetched live from OpenAlex

Dandelion, with its unique wind dispersal mechanism, can easily spread its seeds across vast land areas, encroaching on territories of other creatures. To address this issue, two models are considered: The first model considers wind patterns, temperature, and moisture in dandelion growth, using differential equations to analyze population changes over time. Sensitivity analysis reveals the model’s responsiveness to these factors. The second model combines ecological and economic factors to assess the impact of invasive species, employing fuzzy mathematics to determine the severity of impact. The study identifies Canada Goldenrod as particularly destructive. These models offer insights for future invasive species management policies, showcasing innovations in incorporating partial differential functions and fuzzy mathematics for more accurate estimations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.004
GPT teacher head0.245
Teacher spread0.241 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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