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Record W2947229153 · doi:10.15273/pnsis.v50i1.8873

The marine macroalgae of Brier Island, Nova Scotia, Canada

2019· article· en· W2947229153 on OpenAlexafffundvenueabout
David J. Garbary, C. J. Bird, Beverly Hymes, H. Vandermeulen

Bibliographic record

VenueProceedings of the Nova Scotian Institute of Science · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsBedford Institute of OceanographyDalhousie UniversitySt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeographySpecies richnessEcologyBayAlgaeBiologyArchaeology

Abstract

fetched live from OpenAlex

From May to October 2017 seaweeds were identified in the field and laboratory from 20 sites around Brier Island, Nova Scotia. While most sites were intertidal rocky shores, there were one small salt marsh and one eelgrass bed included in the study, and some subtidal sampling was conducted utilizing SCUBA and snorkeling. The Brier Island seaweeds comprised 152 species and varieties of which 62 were Rhodophyta, 44 were Chlorophyta, 44 were Phaeophyceae, and two species were Xanthophyceae. Three species were new records for eastern Canada: Colaconema bonne- maisoniae, C. endophyticum, and Elachista stellaris, all were pre- viously recorded from New England. The flora included eight non- native species of which Colpomenia peregrina and Bonnemaisonia hami- fera (both gametophytic and tetrasporophytic stages) were abundant at two or more sites, and the invasive Codium fragile subsp. fragile was recorded based on a single drift specimen. With 150 species and varieties of seaweeds, Brier Island has the highest species richness of a limited area of eastern Canada. The Cheney floristic index at 2.4 is higher than comparable areas, and suggests that many additional brown algae remain to be found.Keywords: Chlorophyta, Colaconema, Bay of Fundy, Brier Island, Phaeophyceae, Rhodophyta, seaweeds

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)0.001
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 score0.117
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.189
Teacher spread0.181 · 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

Citations5
Published2019
Admission routes4
Has abstractyes

Explore more

Same venueProceedings of the Nova Scotian Institute of ScienceSame topicMarine and coastal plant biologyFrench-language works237,207