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Record W6892196771 · doi:10.5061/dryad.d149b

Data from: Lichen biodiversity and ecology in the San Bernardino and San Jacinto Mountains in southern California (U.S.A.)

2017· dataset· en· W6892196771 on OpenAlexaboutno aff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2017
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsLichenTaxonBiodiversityEndemismSynonym (taxonomy)

Abstract

fetched live from OpenAlex

San Bernardino National Forest in southern California encompasses two major mountain ranges, the San Bernardino Mountains and the San Jacinto Mountains. Here 414 taxa of lichenized fungi are reported from San Bernardino National Forest as a whole; 327 from the San Jacinto Mountains (including the Santa Rosa Mountains), and 289 from the San Bernardino Mountains. Two species new to science are described: Lecanora remota and Lecidea stratura. Two undescribed taxa of Bellemerea and Scytinium are reported, both currently under study. Five species are reported new for North America and California: Gloeoheppia rugosa, Lecanora formosa, Peccania cernohorskyi, P. corallina and Psorotichia vermiculata. Peccania cernohorskyi is also reported new for Canada (British Columbia). Eight species are reported new for California: Caloplaca diphasia, C. isidiigera, Peltigera extenuata, Rhizocarpon simillimum, Rinodina lobulata, R. terrestris, Sarcogyne squamosa, and Xylographa difformis. Lecidea xanthococcoides is recognized as a synonym of Lecanora cadubriae. The California endemic Lecidea kingmanii is reported as producing 4-0-demethylplanaic acid. Polysporina simplex is treated as Acarospora simplex and P. urceolata as A. urceolata. The new combination Acarospora gyrocarpa is proposed for Polysporina gyrocarpa.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.197
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.289
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2017
Admission routes1
Has abstractyes

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