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Record W4394882318 · doi:10.1639/0747-9859-41.1.9

Bursting the Stubble Bubble: Citizen Scientists Measure Ecological Continuity Near Goldsmith Lake, Nova Scotia Using Calicioid Lichens and Fungi

2024· article· en· W4394882318 on OpenAlexaboutno aff
Ashlea Viola, Nina Newington, Jonathan Riley, Steven B. Selva, Lisa Proulx

Bibliographic record

VenueEvansia · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaLichenEcologyMeasure (data warehouse)GeographyArchaeologyEnvironmental scienceBiologyComputer science

Abstract

fetched live from OpenAlex

In an effort to protect a forest on provincial land near Goldsmith Lake in Annapolis County, Nova Scotia, from timber harvest operations, a group of citizen scientists began documenting the biodiversity of the area. In December 2022, the group invited Dr. Steven Selva, a lichenologist specializing in calicioid lichens and fungi, to visit and teach them how to locate and collect calicioid specimens. We found 27 calicioid species, one of which was new to the Maritimes, providing additional evidence that the forest is rich in biodiversity and that the areas recognized as old-growth were larger than the provincial government had previously realized.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.438
Threshold uncertainty score0.882

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.254
Teacher spread0.223 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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