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Record W2016420435 · doi:10.1016/j.crpv.2010.11.002

Amber microfossils: On the validity of species concept

2011· article· en· W2016420435 on OpenAlexaff
Vincent Girard, Sina M. Adl

Bibliographic record

VenueComptes Rendus Palevol · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFossil Insects in Amber
Canadian institutionsDalhousie University
FundersAgence Nationale de la Recherche
KeywordsExtant taxonFossil RecordBiologyPaleontologyEvolutionary biology

Abstract

fetched live from OpenAlex

Do terrestrial micro-organisms evolve morphologically? A recent concept suggests that morphological stasis over dozens of millions of years has persisted in microbial lineages. However, it is based on a weak fossil record. Indeed, it is already difficult to define a species with extant microbes, and this task is even harder when dealing with fossil micro-organisms. Based on research on fossils in amber, we highlighted the different problems that are raised when describing a new fossil species of micro-organisms and we discuss the concept of morphological stasis. Les micro-organismes terrestres évoluent-ils morphologiquement ? Un concept récent suggère que des stases morphologiques (plusieurs dizaines de millions d’années) existent chez différents groupes de micro-organismes. Cependant, il est basé sur un registre fossile très critiquable. En effet, il est difficile de définir une espèce à partir de micro-organismes actuels, et cette tâche devient encore plus ardue, lorsqu’il s’agit de micro-organismes fossiles. Grâce aux recherches sur l’ambre, nous avons souligné les différents problèmes qui surviennent lors de la description d’une nouvelle espèce de micro-organismes fossiles et nous avons discuté le concept de stase morphologique.

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)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.037
Scholarly communication0.0050.014
Open science0.0020.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.152
GPT teacher head0.236
Teacher spread0.084 · 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 designTheoretical or conceptual
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

Citations24
Published2011
Admission routes1
Has abstractyes

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Same venueComptes Rendus PalevolSame topicFossil Insects in AmberFrench-language works237,207