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Evolution of Reproductive Proteins

2016· reference-entry· en· W2789875654 on OpenAlexaff

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsBiologyEvolutionary biologyIdentification (biology)Reproductive successGenetic FitnessMolecular evolutionBiological evolutionGenetic algorithmReproductionVariation (astronomy)Reproductive isolationTaxonAdaptive evolutionGeneGeneticsPhylogeneticsEcologyPopulationDemography

Abstract

fetched live from OpenAlex

Evolutionary geneticists have long been interested in the identification of variation at the molecular level, as evolution itself requires the existence of heritable differences among organisms. Thus, detecting gene variants and measuring differences in rates of change among such variants have been important subjects of study among evolutionary geneticists. Reproduction is also a topical subject in evolutionary biology because fitness is a function of reproductive success. Moreover, limitations in gene flow imposed by either premating or postmating reproductive barriers are major contributors to the evolution of new species. Since the early 1980s the study of the evolution of reproductive proteins in a wide variety of taxa has revealed them to be among the most rapidly evolving genes. This observation has led researchers to test different alternative hypotheses that can explain this rapid rate of evolution.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.014
GPT teacher head0.238
Teacher spread0.223 · 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
GenreOther

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

Citations2
Published2016
Admission routes1
Has abstractyes

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