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Record W7110289622 · doi:10.1162/isal.a.887

ProtoCell: a computational protocell model implemented using <i>String</i>

2025· article· W7110289622 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

VenueALIFE · 2025
Typearticle
Language
FieldPhysics and Astronomy
TopicOrigins and Evolution of Life
Canadian institutionsConcordia University
Fundersnot available
KeywordsProtocellRibozymeString (physics)Encoding (memory)Factory (object-oriented programming)SoundnessCode (set theory)Computational model

Abstract

fetched live from OpenAlex

A computer language called String (Islam et al., 2022) was originally designed for the purpose of manual authoring and computational evolution of the active entities (called ‘ribozymes’) within a new computational protocell model (called ProtoCell). String’s source code (or ‘phenotype’) has an assembly-like format, while its encoding (or ‘genotype’) has the form of an RNA sequence. In this paper, we present, in brief, the complete ProtoCell model, comprising three essential subsystems, all utilizing ribozymes written in String. The first or, Genomic subsystem is made of a single loop of RNA, which has the encodings of all the ribozymes of the model. The Membrane subsystem is made of a self-assembling lipid, with embedded trans-membrane transporters, realized as ribozymes. The last sub-system is the Metabolism, the factory of the cell, where all the necessary building blocks, and energy molecule, are synthesized in reactions catalyzed by ribozymes. We combined all three subsystems to achieve a stable ProtoCell simulation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.874
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.342
Teacher spread0.312 · 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