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Rare Epiphytic Coastal Lichen Habitats, Modeling, and Management in the Pacific Northwest

2005· article· en· W2172599777 on OpenAlexaboutno aff
Doug A. Glavich, Linda H. Geiser, Alexander G. Mikulin

Bibliographic record

VenueThe Bryologist · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
FundersU.S. Forest ServiceU.S. Fish and Wildlife ServiceWashington State University
KeywordsLichenEpiphyteHabitatBayEcologyGeographyBiologyArchaeology

Abstract

fetched live from OpenAlex

The ecological amplitudes, associated lichens, and substrates of fifteen regionally rare coastal epiphytic lichens (Bryoria pseudocapillaris, B. spiralifera, B. subcana, Erioderma sorediatum, Heterodermia leucomela, Hypotrachyna revoluta, Leioderma sorediatum, Leptogium brebissonii, Niebla cephalota, Pannaria rubiginosa, Pseudocyphellaria perpetua, Pyrrhospora quernea, Ramalina pollinaria, Teloschistes flavicans, and Usnea hesperina) in 85 randomly-selected and 49 purposively-selected 0.04 ha circular plots along a 5 km wide strip of Pacific coastline from San Francisco Bay to the U.S.-Canadian border are reported. Logistic regression, used to identify environmental variables most indicative of suitable habitat, indicated that small changes in climate and forest type strongly affected probability of occurrence for many species. Threats to coastal lichens, including climate change, are discussed. The findings can be used to aid discovery of additional populations and manage existing habitat.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.456

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.224
Teacher spread0.201 · 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 designSimulation or modeling
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

Citations29
Published2005
Admission routes1
Has abstractyes

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