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Spiders (Araneae) associated with downed woody material in a deciduous forest in central Alberta, Canada

2001· article· en· W2097138177 on OpenAlexafffundabout
Christopher M. Buddle

Bibliographic record

VenueAgricultural and Forest Entomology · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpiderForest floorHabitatDeciduousEcologyBiologyFaunaLinyphiidaeEcosystem

Abstract

fetched live from OpenAlex

Abstract 1 Spiders (Araneae) were collected on and near downed woody material (DWM) in a Populus ‐dominated forest to determine if spiders utilize wood surfaces, and to ascertain the importance of DWM habitat and wood elevation for spider assemblages. 2 Over 10 000 spiders representing 100 species were collected. Although more spiders were collected on the forest floor, spider diversity was higher in traps located on wood surfaces than on the forest floor, and 11 species were collected more frequently on wood surfaces. 3 Spiders utilized DWM at different stages in their development. Female Pardosa mackenziana (Keyserling) (Lycosidae) carrying egg sacs were caught most often on the surface of DWM, possibly to sun their egg sacs. Additionally, the proportion of immature spiders was higher on the wood surface than on the forest floor. 4 Spiders collected on logs with and without bark were compared to assemblages collected on telephone poles to assess what features of DWM habitat may be important. Web‐building species were seldom collected on telephone poles, suggesting that they depend on the greater habitat complexity provided by DWM. In contrast, hunting spiders did not distinguish between telephone poles and logs. 5 Fewer spiders and a less diverse fauna utilized elevated compared to ground‐level wood. Additionally, Detrended Correspondence Analysis revealed that the spider community from elevated wood was distinguishable from the spider community from ground‐level wood, and from the forest floor spider community.

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 score0.270
Threshold uncertainty score0.332

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 studies0.0000.000
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 head0.008
GPT teacher head0.166
Teacher spread0.158 · 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

Citations50
Published2001
Admission routes3
Has abstractyes

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