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Record W2565457688 · doi:10.1101/096701

A network theory of the origin of life

2016· preprint· en· W2565457688 on OpenAlexaff
Geoffrey W. Hoffmann

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2016
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicOrigins and Evolution of Life
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNucleationEvent (particle physics)Context (archaeology)AbiogenesisBiologyComputer scienceEvolutionary biologyStatistical physicsPhysicsGeneticsPaleontologyAstrophysics

Abstract

fetched live from OpenAlex

Abstract The origin of life may have been a low probability event that involved both RNA and polypeptides. While such an event would occur with low probability, the probability is not too low in the context of the number of nucleation opportunities on the primitive Earth. The probability for the nucleation event is too small if needed components occur as frequently as disruptive components do, without specific interactions between the two classes. However, if many of the needed components contribute by inhibiting otherwise disruptive components, a high probability for a complex nucleation as the beginning of life event emerges. RNA interference and long non-coding RNAs are ascribed roles in inhibiting components that would otherwise be disruptive in the context of a nucleation event. The theory likewise provides an inhibitory role for the large fraction of proteins (35% to 40%) that have no known function in both prokaryotes and eukaryotes. It is suggested that volcanic ash could provide the large number of random shapes needed as the basis for the nucleation event. Experiments based on that hypothesis are proposed.

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 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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.214
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2016
Admission routes1
Has abstractyes

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