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Record W7100643069

ii Invasive Earthworm (Oligochaeata: Lumbricidae) Populations in varying Vegetation Types on a Landscape- and Local-scale

2012· article· en· W7100643069 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsEarthwormVegetation (pathology)EpigealAbundance (ecology)HabitatVegetation typeDeciduousEcotone
DOInot available

Abstract

fetched live from OpenAlex

There have been no landscape-scale studies on earthworm populations in Canada comparing vegetation types; previous studies on edge habitats have been conducted in agricultural systems. I examined the spatial variations of earthworm populations by measuring abundance based on regional municipality, vegetation type, and edge habitat. Earthworms were sampled throughout the season across a gradient of vegetation types including meadow, forest edge, and interior at a local-scale; and at the landscape level with vegetation types including meadow, deciduous forest, pine plantation and mixed forest. Regional effects were more significant than vegetation type likely due to a gradient of soil characteristics in southern Ontario; edges had intermediate earthworm abundance and a higher proportion of epigeic species. My research provides insight into the patterns of earthworm populations in southern Ontario and the possible effects of edge creation through landscape fragmentation. Field sampling of earthworm parasitoid cluster-flies (Calliphoridae: Pollenia) using synomones was also discussed. iii

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)0.000
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 score0.452
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.223
Teacher spread0.188 · 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
Published2012
Admission routes1
Has abstractyes

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