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Record W2791530428 · doi:10.11575/prism/10212

Terrestrial snails as indicators of the health of the decomposer part of the ecosystem in Parks in Alberta

2008· article· en· W2791530428 on OpenAlexfundaboutno aff
Stuart A. Harris

Bibliographic record

VenueOpen MIND · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMollusks and Parasites Studies
Canadian institutionsnot available
FundersParks Canada
KeywordsDecomposerEcosystemEcosystem healthEcologyEnvironmental scienceTerrestrial ecosystemGeographyEcosystem servicesBiology

Abstract

fetched live from OpenAlex

Land snails are a part of the decomposer group of organisms in the upper part of the soil which is normally ignored when considering Parks management.The land snails consist of a relatively small number of species that entered the area after the last glaciation, following the northward migration of the boreal forest, and also a second even rarer group of species that entered the area during the Hypsithermal event.Ecologically, the snails can be divided into four groups, viz., the turf species, the duff species, the wetland species and the generalists.They can only survive along the galleria forest along the main rivers, and in areas with trees or tall grass prairie up to about 1900 m elevation.Frequent ground fires largely destroy the terrestrial molluscan fauna in the grassland sites.Duff faunas are less affected.During revegetation, generalists may invade the area together with the duff specialists that will become dominant after a suitable organic layer has become established on the forest floor.Wetland species often survive fire.Other major threats are destruction of habitat, introduction of nonnative vegetation, development of recreational parks, urban and resource development and agriculture.

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 score0.128
Threshold uncertainty score0.258

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 communication0.0010.000
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 head0.042
GPT teacher head0.285
Teacher spread0.243 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

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