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Record W4379928204 · doi:10.3176/earth.2023.21

Chitinozoan nomenclature and databases

2023· article· en· W4379928204 on OpenAlexaboutno aff
Steven Camina, Olle Hints, Anthony Butcher

Bibliographic record

VenueProceedings of the Estonian Academy of Sciences Geology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsNomenclatureDatabaseComputer scienceInformation retrievalBiologyZoologyTaxonomy (biology)

Abstract

fetched live from OpenAlex

In 1930, Alfred Eisenack suggested the term ‘chitinozoan’ for a microfossil group that he discovered from erratic boulders on the Baltic Sea coast. They are known from the Early Ordovician until the end of the Devonian and have a broad paleogeographic distribution in marine deposits. Even though they are useful biostratigraphy markers, their biological affinity is unknown. Several theories have been proposed through the years, with the most widely accepted to date being that they are the eggs of soft-bodied metazoans. Nevertheless, some studies suggest that chitinozoans are fossils of individual microorganisms (protists) rather than of metazoan origin. The aim of this contribution is to summarize the advantages of the current chitinozoan classification and analyze the status quo of the current chitinozoan databases in order to make the classification less subjective and data more accessible. Since the beginning of their study, chitinozoan workers have used a binominal taxonomy describing genera and species based on morphological features. In 1999, Florentin Paris and co-authors introduced a revised suprageneric classification regulated by the International Code of Zoological Nomenclature (ICZN), which proved very efficient and has since been followed by all workers on this group. According to the ICZN, the concept of ‘species’ is the only one that refers to an actual population or entity and all higher categories are abstract entities. This means that any feature can be selected to separate the genera and families. In chitinozoans, scanning electron microscope (SEM) images are used to distinguish morphologic features such as the vesicle, aperture, neck, and ornamentation. These main characteristics were used as the basis of classification. The category of ‘Order’ is not regulated by the ICZN; however, in 1972, Eisenack proposed the useful subdivisions of ‘Operculatifera’ and ‘Prosomatifera’ that have been maintained until today. This classification gives stability to the nomenclature, prevents overlap of generic descriptions, and provides a framework for phylogenetic analysis. It was highlighted by the authors of this classification that a computer-assisted system of identification could be developed if a digital taxonomic database were available. There are several databases with the potential to be useful for chitinozoan taxonomic classification. ZooBank is the official registry of the ICZN. It records nomenclatural acts and includes the original descriptions of new scientific names and their publications. For occurrence-based paleontological records, the Paleobiology Database and the Geobiodiversity Database are extremely useful. Both have an intuitive and simple interface for the user to see the taxa distribution and taxonomic information. These three databases complement each other, but they either have few chitinozoan records or lack complete taxonomic information. There is a desktop taxonomic database CHITINOVOSP for chitinozoans, designed by Florentin Paris, which has proven to be useful but needs to be purchased. Achab et al. developed in Canada another chitinozoan database CHITINOS that is not currently used. The most complete and useful chitinozoan database at present seems to be CHITDB, where browsing and searching for chitinozoan taxa, samples, sections, references, and SEM images is simple. However, it is focused only on material from the Baltic region. Databases such as the Encyclopedia of Life, the Catalogue of Life and the World Register of Marine Species lack chitinozoan records but they are collaborative and provide free global access to knowledge. This collaborative formula seems to be efficient enough to have a trusted digital source of information. Since at present the taxonomic classification of chitinozoans is no longer under discussion and it has proven to be workable, the following step for chitinozoan researchers would be to have a complete database. We believe that a collaborative effort should be made as there are only a few specialists in the area nowadays. It is not crucial which database should be completed, but it should be useful, as complete as possible, and freely accessible. In particular, we believe that the Baltic CHITDB database is an excellent starting platform to achieve that goal in the near future.

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)0.002
metaresearch head score (Gemma)0.013
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0320.039
Science and technology studies0.0020.001
Scholarly communication0.0070.005
Open science0.0040.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.020

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 head0.337
Teacher spread0.306 · 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
GenreMethods

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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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