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Record W7005681005

A Revision of the Genus Cryptonemia (Halymeniaceae, Rhodophyta) in Bermuda, Western Atlantic Ocean, Including Five New Species and C. bermudensis (Collins & M. Howe) comb. nov [post-print]

2018· article· en· W7005681005 on OpenAlexfundno aff

Bibliographic record

VenueTrinity College Digital Repository (Trinity College) · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDana FoundationNew Brunswick Innovation FoundationDivision of Environmental BiologyU.S. Department of AgricultureOffice of Experimental Program to Stimulate Competitive ResearchNational Science Foundation
KeywordsPhylogenetic treeFlora (microbiology)Ribosomal DNAPhylogeneticsGenusRibosomal RNATaxonomy (biology)
DOInot available

Abstract

fetched live from OpenAlex

Cryptonemia specimens collected in Bermuda over the past two decades were analysed using gene sequences encoding the large subunit of the nuclear ribosomal DNA and the large subunit of RuBisCO as genetic markers to elucidate their phylogenetic positions. They were additionally subjected to morphological assessment and compared with historical collections from the islands. Six species are presently found in the flora including C. bermudensis comb. nov., based on Halymenia bermudensis, and the following five new species: C. abyssalis, C. antricola, C. atrocostalis, C. lacunicola and C. perparva. Of the eight species known in the western Atlantic flora prior to this study, none is found in Bermuda. Specimens reported in the islands in the 1900s attributed to C. crenulataand C. luxurians are representative of the new species, C. antricola and C. atrocostalis, respectively.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.046
GPT teacher head0.234
Teacher spread0.188 · 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
Published2018
Admission routes1
Has abstractyes

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