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Record W4389951389 · doi:10.3389/fevo.2023.1326379

Path-dependent selection—a bridge between natural selection and neutral selection

2023· article· en· W4389951389 on OpenAlexaff
Rui‐Wu Wang, Yun-Yun Yu, An-Na Shi, Qi-Kai Zhu, Minlan Li, Chao Wang, Yi Tao, Jia‐Xu Han

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of British Columbia
FundersNanjing UniversityNational Science Fund for Distinguished Young ScholarsChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsSelection (genetic algorithm)Natural selectionPath (computing)RandomnessFrequency-dependent selectionComputer scienceStatistical physicsEvolutionary biologyMathematicsBiologyPhysicsArtificial intelligenceStatistics

Abstract

fetched live from OpenAlex

Path-dependent selection follows the premise of complete symmetry in the neutral theory of selection; mutations in the natural world are entirely based on statistical randomness, lack directionality, and thus do not exhibit differences in fitness. Under specific spatiotemporal conditions, however, evolutionary positive feedback effects resulting from the specific environment will result in the breakdown of symmetry pre-assumed in neutral selection. This evolutionary positive feedback, a recursive effect, is of Lamarckian active selection or inheritance of acquired characteristics. The mutual antagonistic interactions between the positive selection of recursive effect and the passive selection under natural selection pressure of the environment in multidimensional conditions will result in evolutionary paths. Path-dependent selection proposes that the evolutionary process of organisms is a selection process based on path frequencies rather than an increase in fitness, with a strong reliance on the paths that it has taken in the past. Because of the existence of transition probabilities between different paths or within the same path (such as plasmid transfer, transposons, and function transfer in ecological interactions), path formation will exhibit acceleration or deceleration effects, explaining Gould’s principles such as punctuated equilibrium. When environmental selection pressure is weak or zero, most or all paths (like neutral selection outcomes) may be possible. The frequencies of different paths will differentiate as environmental selection increases, and the paths with higher frequencies will be more easily selected. When the evolutionary process or history has no impact on the evolution of the paths themselves (a static, equilibrium state), the path with the highest frequency is the shortest or optimal path used by evolution—a result consistent with Darwin’s theory of natural selection. Path-dependent selection, which draws inspiration from modern physics, particularly path integral methods in quantum mechanics, may provide us with a new perspective and approach to explaining the evolution of life.

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)0.007
metaresearch head score (Gemma)0.013
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 score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.013
Scholarly communication0.0050.007
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.004
GPT teacher head0.223
Teacher spread0.218 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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