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Record W7075609180

Carabid beetle assemblages (Coleoptera, Carabidae) across urban-rural gradients : an international comparison

2002· article· en· W7075609180 on OpenAlexaboutno aff

Bibliographic record

VenueTyöväentutkimus Vuosikirja · 2002
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatEctothermSpecies richnessPredationEcosystemVegetation (pathology)
DOInot available

Abstract

fetched live from OpenAlex

We studied communities of carabid beetles in residual forest patches along urban-suburban-rural gradients in three cities (Helsinki, Finland; Sofia, Bulgaria and Edmonton, Canada) to examine their responses to urbanisation. Only Finnish carabids showed a marked division of community structure along the gradient. In Bulgaria and Canada, carabids did not separate into distinct urban, suburban and rural communities. Our results provide some support for the predictions that species richness will decrease, that opportunistic species will gain dominance, and that small-sized species will become more numerous under disturbance such as that provided by urbanisation. The rather weak and varied response of carabids to this disturbance suggests that local factors and their interaction are of primary importance for community composition. Occurrence of reasonably similar carabid communities across the gradient at each of the three levels of urbanisation suggests that habitat changes commonly associated with urbanisation have not affected the ecological integrity of carabid assemblages in residual urban forest patches.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.281
Teacher spread0.250 · 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
Published2002
Admission routes1
Has abstractyes

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