MétaCan
Menu
Back to cohort
Record W2138657788 · doi:10.1139/b04-114

Macrofungi from six habitats over five years in Clayoquot Sound, Vancouver Island

2004· article· en· W2138657788 on OpenAlexvenueaboutno aff
Christine Roberts, Oluna Ceska, Paul Kroeger, Bryce Kendrick

Bibliographic record

VenueCanadian Journal of Botany · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
FundersAndrew W. Mellon Foundation
KeywordsHabitatEcologyGeographyRainforestBiodiversityBogSand dune stabilizationBiologyPeat

Abstract

fetched live from OpenAlex

Over 5 years, macrofungi from six habitats in Clayoquot Sound, Vancouver Island, British Columbia, were documented. Habitats were categorized as dune, spruce fringe, old-growth rainforest, second-growth forest, bog, or estuarine. All but the second-growth forest are natural ecosystems. A total of 551 taxa of macrofungi were recorded. Between 17% and 36% of the species in any one habitat were found only in that habitat. The most frequently encountered and ubiquitous species was Craterellus tubaeformis (Fr.) Quel., found in all years, habitats, and sites. Of the 551 taxa, only 28 were found every year, and 308 were found in only 1 year. Rare species that were recorded include Cordyceps ravenelii Berkeley & Curtis, Hygrophorus inocybiformis Smith, and Tricholoma apium Schaeffer in the dunes and Stereopsis humphreyi (Burt) Redhead in the spruce fringe. Similarities between habitats based on taxa in common showed that bog and estuarine habitats had only 9%–17% in common with each other and the other habitats, whereas dune, spruce fringe, and the two forest types shared 21%–31% of their species. Old-growth rainforest yielded approximately 4 times as many species as bog and estuarine habitats, and approximately 1.5 times as many as the other three habitats.Key words: Clayoquot Sound, Vancouver Island, macrofungi, habitats, biodiversity.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score1.000

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)0.0010.000

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 head0.008
GPT teacher head0.194
Teacher spread0.185 · 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.

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

Citations30
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of BotanySame topicLichen and fungal ecologyFrench-language works237,207