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Record W2106957252 · doi:10.2216/11-89.1

A review of recent freshwater dinoflagellate cysts: taxonomy, phylogeny, ecology and palaeocology

2012· review· en· W2106957252 on OpenAlexfundno aff
Kenneth Neil Mertens, Karin Rengefors, Øjvind Moestrup, Marianne Ellegaard

Bibliographic record

VenuePhycologia · 2012
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
FundersUniversiteit GentUniversité du Québec à MontréalUniversidade de Aveiro
KeywordsDinoflagellateBiologyBiological dispersalEcologyTaxonomy (biology)PhylogeneticsZoology

Abstract

fetched live from OpenAlex

Mertens K.N., Rengefors K., Moestrup Ø. and Ellegaard M. 2012. A review of recent freshwater dinoflagellate cysts: taxonomy, phylogeny, ecology and palaeocology. Phycologia 51: 612–619. DOI: 10.2216/11-89.1Resting stages (e.g. cysts) play an important role in the life history and ecology of phytoplankton, e.g. the survival, reproduction, genetic recombination, and dispersal of many species. Marine dinoflagellates cysts have been intensively studied by both geologists and biologists, but freshwater cysts have received less attention. There are approximately 350 freshwater dinoflagellate species, and resting cysts have been described for 84 species. We evaluated the descriptions, and we reproduced images for each cyst type. The review highlighted the importance of cyst characters for taxonomy and phylogeny. We suggested that shape, wall ornamentation and possibly the archeopyle and color were important morphological characteristics at the generic level and above. The ecology of freshwater dinoflagellate cysts was reviewed, and the ecological role of cysts was discussed. The potential of freshwater cysts for Quaternary palaeoecological reconstructions was highlighted, revealing that these could serve as useful indicators of temperature, pH and productivity.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.001

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 head0.076
GPT teacher head0.272
Teacher spread0.196 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations68
Published2012
Admission routes1
Has abstractyes

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