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Record W2106855946 · doi:10.1098/rsbl.2013.0215

The incidental response to uniform natural selection

2013· article· en· W2106855946 on OpenAlexaff
Graham Bell

Bibliographic record

VenueBiology Letters · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyUncorrelatedReplicateNatural selectionSelection (genetic algorithm)Evolutionary biologyRange (aeronautics)ChlamydomonasPopulationEcologyGeneticsStatisticsGeneDemographyArtificial intelligence

Abstract

fetched live from OpenAlex

When populations are exposed to novel conditions of growth, they often become adapted to a similar extent, and at the same time, evolve some degree of impairment in their original environment. They may also come to vary widely with respect to characters which are uncorrelated with fitness, as the result of chance genetic associations among the founders, when these are a small sample from a large and variable ancestral population. I report an experiment in which 240 replicate lines of the unicellular chlorophyte Chlamydomonas were derived from primarily photoautotrophic ancestors and cultured as heterotrophs in the dark. All adapted to the dark and were impaired in the light after several hundred generations of culture. They also displayed a wide range of colony morphologies that were uncorrelated with fitness. This incidental response to selection probably arose through random variation in the initial composition of the lines. The differences between closely related species or varieties may likewise arise, in similar circumstances, by sampling error rather than natural selection.

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)0.005
metaresearch head score (Gemma)0.027
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.003
GPT teacher head0.204
Teacher spread0.200 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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