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Record W2388751865

ADVANCES IN PHYLOGENETIC CHRONOLOGY

2009· article· en· W2388751865 on OpenAlexaff
Qun Yang

Bibliographic record

VenueGushengwu xuebao · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMolecular clockContext (archaeology)Phylogenetic treeChronologyPaleontologyEarth historyEvolutionary biologyBiologyEcologyPhylogenetics
DOInot available

Abstract

fetched live from OpenAlex

Phylogenetic chronology,or phylochronology,has become an active research area in evolutionary biology.With phylogenetic divergence dates established for the evolutionary history,the biotic evolution and the phylogenetic steps may be comprehended in the context of the physical environmental changes during the earth history.It is emphasized herein that the integrative approach of fossil dates and the relaxed molecular clock techniques would yield a better picture of the evolutionary timescale or a more precise and more accurate phylochronograms for organism groups than if only fossil dates or only molecular timescales are considered.A consensus timescale with both molecular dates and fossil constraints is preferred and,furthermore,an interpretation for the evolutionary schemes thus established should be done in the context of the geological backgrounds;in other words,the evolutionary timescale is laid out as the timeframe for the coevolutionary history between life and the Earth's physical environment.We present recent development in molecular dating techniques based on the relaxed molecular clock concept and strategies in fossil calibration.Examples in recent development of animal phylochronology and estimation of the dates of early invertebrate animal landing are discussed with the integration of fossil dates,molecular chronology,and geological backgrounds.We stress the importance of fossil dates as the foundation for phylochronology and geological background as probable mechanisms for phylogenetic divergences or radiations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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 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

Citations1
Published2009
Admission routes1
Has abstractyes

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