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Record W7135961426

Economical impact of invasion IAS

2016· dissertation· cs· W7135961426 on OpenAlexaboutno aff
Lukáš Tyrpekl

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2016
Typedissertation
Languagecs
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsnot available
Fundersnot available
KeywordsBalsamHabitatBiodiversityEcosystemNatural (archaeology)Economic impact analysisInvasive species
DOInot available

Abstract

fetched live from OpenAlex

The invasion of plants and animals species are considered as one of the main danger for diversity of natural ecosystems worldwide. With destruction of habitats represent the main reason of the current global wave of taxa extinctions. The obviousness of biological invasions are financial costs in different branches connected with their prevention and liquidation. The main purpose of this master thesis was to evaluate the economic impacts of invasion of the selected invasive species, concretely Grand hogweed (Heracleum mantegazzianum), Himalayan balsam (Impatiens glandulifera), Giant goldenrod and Canadian (Solidago gigantea and canadensis) and also Japanese knotweed, Giant knotweed and Bohemian knotweed (Reynoutria japonica, sachalinensis and × bohemica). As an area of interest was Třeboňsko chosen, where the economic impact of these invasive species based on the results of field investigation was evaluated with in cooperation with an owners of the affected land. Also, ecosystem damage were registered and total financial damage was estimated.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.001

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 head0.014
GPT teacher head0.244
Teacher spread0.229 · 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 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
Published2016
Admission routes1
Has abstractyes

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