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Record W2060005977 · doi:10.1139/g02-050

Genome size and developmental parameters in the homeothermic vertebrates

2002· article· en· W2060005977 on OpenAlexafffundvenue
T. Ryan Gregory

Bibliographic record

VenueGenome · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Guelph
KeywordsBiologyGenome sizeGenomeEvolutionary biologyLongevityVertebrateGenome evolutionPloidyGeneticsGene

Abstract

fetched live from OpenAlex

Although unrelated to any intuitive notions of organismal complexity, haploid genome sizes (C values) are correlated with a variety of cellular and organismal parameters in different taxa. In some cases, these relationships are universal--notably, genome size correlates positively with cell size in each of the vertebrate classes. Other relationships are apparently relevant only in particular groups. For example, although genome size is inversely correlated with metabolic rate in both mammals and birds, no such relationship is found in amphibians. More recently, it has been suggested that developmental rate and (or) longevity are related to genome size in birds. In the present study, a large dataset was used to examine possible relationships between genome size and various developmental parameters in both birds and mammals. In neither group does development appear to be of relevance to genome size evolution (except perhaps indirectly in birds through the intermediation of body size and (or) within the rodents), a situation very different from that found in amphibians. These findings make it clear that genome size evolution cannot be understood without reference to the particular biology of the organisms under study.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.187
Teacher spread0.167 · 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 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

Citations50
Published2002
Admission routes3
Has abstractyes

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