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The Prokaryote-Eukaryote Dichotomy: Meanings and Mythology

2005· review· en· W2166579540 on OpenAlexaff
Jan Sapp

Bibliographic record

VenueMicrobiology and Molecular Biology Reviews · 2005
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsYork University
Fundersnot available
KeywordsProkaryoteBiologyEukaryoteContext (archaeology)PhylogeneticsPhylogenetic treeEpistemologyEvolutionary biologyZoologyPhilosophyGeneticsGenomeBacteriaPaleontology

Abstract

fetched live from OpenAlex

Drawing on documents both published and archival, this paper explains how the prokaryote-eukaryote dichotomy of the 1960s was constructed, the purposes it served, and what it implied in terms of classification and phylogeny. In doing so, I first show how the concept was attributed to Edouard Chatton and the context in which he introduced the terms. Following, I examine the context in which the terms were reintroduced into biology in 1962 by Roger Stanier and C. B. van Niel. I study the discourse over the subsequent decade to understand how the organizational dichotomy took on the form of a natural classification as the kingdom Monera or superkingdom Procaryotae. Stanier and van Niel admitted that, in regard to constructing a natural classification of bacteria, structural characteristics were no more useful than physiological properties. They repeatedly denied that bacterial phylogenetics was possible. I thus examine the great historical irony that the "prokaryote," in both its organizational and phylogenetic senses, was defined (negatively) on the basis of structure. Finally, we see how phylogenetic research based on 16S rRNA led by Carl Woese and his collaborators confronted the prokaryote concept while moving microbiology to the center of evolutionary biology.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.310
Teacher spread0.291 · 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

Citations188
Published2005
Admission routes1
Has abstractyes

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