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How biological codes break causal chains to enable autonomy for organisms

2023· article· en· W4386278166 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBiosystems · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrigins and Evolution of Life
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsComputer scienceCyberneticsTheoretical computer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Autonomy, meaning freedom from exogenous control, requires independence of both constitution and cybernetic regulation. Here, the necessity of biological codes to achieve both is explained, assuming that Aristotelian efficient cause is 'formal cause empowered by physical force'. Constitutive independence requires closure to efficient causation (in the Rosen sense); cybernetic independence requires transformation of cause-effect into signal-response relations at the organism boundary; the combination of both kinds of independence enables adaptation and evolution. Codes and cyphers translate information from one form of physical embodiment (domain) to another. Because information can only contribute as formal cause to efficient cause within the domain of its embodiment, translation can extend or restrict the range over which information is effective. Closure to efficient causation requires internalised information to be isolated from the cycle of efficient causes that it informs: e.g. Von Neumann self-replicator requires a (template) source of information that is causally isolated from the physical replication system. Life operationalises this isolation with the genetic code translating from the (isolated) domain of codons to that of protein interactions. Separately, cybernetic freedom is achieved at the cell boundary because transducers, which embody molecular coding, translate exogenous information into a domain where it no longer has the power of efficient cause. Information, not efficient cause, passes through the boundary to serve as stimulus for an internally generated response. Coding further extends freedom by enabling historically accumulated information to be selectively transformed into efficient cause under internal control, leaving it otherwise stored inactive. Code-based translation thus enables selective causal isolation, controlling the flow from cause to effect. Genetic code, cell-signalling codes and, in eukaryotes, the histone code, signal sequence based protein sorting and other code-dependent processes all regulate and separate causal chains. The existence of life can be seen as an expression of the power of molecular codes to selectively isolate and thereby organise causal relations among molecular interactions to form an organism.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.464

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 head0.037
GPT teacher head0.268
Teacher spread0.232 · 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