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Record W2183281331 · doi:10.11646/zootaxa.1546.1.5

The Erotylidae and Endomychidae (Coleoptera: Cucujoidea) of the Maritime Provinces of Canada: New records, zoogeography, and observations on beetle-fungi relationships and forest health

2007· article· en· W2183281331 on OpenAlexaffabout
Christopher G. Majka

Bibliographic record

VenueZootaxa · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsNova Scotia Hospital
Fundersnot available
KeywordsFaunaZoogeographyContext (archaeology)Nova scotiaBiologyEcologyCapeGeographyArchaeology

Abstract

fetched live from OpenAlex

The Erotylidae and Endomychidae of the Maritime Provinces are surveyed. Fifteen species are now known from the region, fourteen in Nova Scotia, seven in New Brunswick, and four on Prince Edward Island. Thirteen new provincial records (seven from Nova Scotia, three from New Brunswick, and three from Prince Edward Island) are reported. Four erotylids, Dacne quadrimaculata (Say), Triplax dissimulator (Crotch), Triplax flavicollis Lacordaire, Triplax macra LeConte; and two endomychids, Rhanidea unicolor (Ziegler) and Lycoperdina ferruginea LeConte, are newly recorded in the Maritime Provinces as a whole. New records of the rare endomychid, Hadromychus chandleri Bousquet & Leschen, are reported. The fauna is examined in a regional zoogeographic context, paying particular attention to the insular faunas of Cape Breton and Prince Edward Islands. Attention is also drawn to the number of species that have been very rarely collected. This apparent scarcity may be related to the long history of forest management in the region, in particular the effects of intensive forestry on the communities of forest fungi on which these species feed and depend. Attention is drawn to the importance of ongoing research to monitor their populations and assess how these species may be employed as indicators of the overall health forest ecosystems.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.778
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.197
Teacher spread0.173 · 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 teacher head, 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

Citations15
Published2007
Admission routes2
Has abstractyes

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