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Parallelism, deep homology, and evo‐devo

2012· article· en· W1953468087 on OpenAlexafffund
Brian K. Hall

Bibliographic record

VenueEvolution & Development · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and History of Science
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsParallelism (grammar)BiologyConvergent evolutionParallel evolutionSophisticationData parallelismHomology (biology)Evolutionary biologyComputer scienceGeneticsPhylogeneticsGeneParallel computing

Abstract

fetched live from OpenAlex

Parallelism has been the subject of a number of recent studies that have resulted in reassessment of the term and the process. Parallelism has been aligned with homology leaving convergence as the only case of homoplasy, regarded as a transition between homologous and convergent characters, and defined as the independent evolution of genetic traits. Another study advocates abolishing the term parallelism and treating all cases of the independent evolution of characters as convergence. With the sophistication of modern genomics and genetic analysis, parallelism of characters of the phenotype is being discovered to reflect parallel genetic evolution. Approaching parallelism from developmental and genetic perspectives enables us to tease out the degree to which the reuse of pathways represent deep homology and is a major task for evolutionary developmental biology in the coming decades.

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)0.002
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.026
Scholarly communication0.0040.007
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.032
GPT teacher head0.209
Teacher spread0.176 · 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

Citations28
Published2012
Admission routes2
Has abstractyes

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