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Heredity as Transmission of Information: Butlerian 'Intelligent Design'

2006· article· en· W2052749081 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCentaurus · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsQueen's University
Fundersnot available
KeywordsHereditySomaInheritance (genetic algorithm)Foundation (evidence)OffspringTransmission (telecommunications)CognitionCognitive scienceComputer scienceBiologyEpistemologyPhilosophyPsychologyHistoryGeneticsNeuroscienceTelecommunications

Abstract

fetched live from OpenAlex

In the 1870s, Ewald Hering and Samuel Butler provided what was, for that time, a scientifically coherent foundation for the Lamarckist view that positive adaptations to the environment acquired during an individual's lifetime can be transmitted to the offspring. Observing that heredity was a form of memory (involving stored information), they distinguished what are now known as genotype and phenotype and proposed that cognitive abilities present in the the most elementary organisms might mediate a transmission of acquired adaptations. While compatible with the then-available facts of evolution, this Butlerian version of 'intelligent design' was rendered less credible by subsequent appreciations of the discrete (discontinuous) inheritance of many phenotypic characters (Mendelism) and of the separation of germ line from soma (Weismanism). However, it can now be seen that 21st-century bioinformatics has 19th-century roots.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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