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Record W2418834094 · doi:10.21775/cimb.014.039

A Perspective on the Mobilization, Localization and Delivery of Molecules in the Crowded Bacterial Cytoplasm

2012· review· en· W2418834094 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Issues in Molecular Biology · 2012
Typereview
Languageen
FieldMedicine
TopicBiofield Effects and Biophysics
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCytoplasmRibosomeCell biologyTranslation (biology)BiologyRNABiophysicsMessenger RNABiochemistryGene

Abstract

fetched live from OpenAlex

It has been assumed that diffusion of molecules in the bacterial cytoplasm is the mechanism that moves molecules in the absence of cytoplasmic streaming. However, is there an undiscovered mechanism present that mobilizes cytoplasm and its molecular contents, and delivers tRNAs to specific ribosomes at specific bacterial cytoplasmic locations? Mobilization of specific tRNA (and also mRNA transcripts and ribosomes) and cell division proteins to specific intracellular locations may suggest that instructions and/or mechanism(s) are needed. The alternative is that molecular crowding in the cytoplasm is sufficient for gentle contact between mRNA, ribosomes and tRNA. Or is it plausible that the bacterial cytoplasm (and its contents) are mobilized with the outcome being more gentle collisions between molecules than by a diffusion only mechanism? One hypothesis is that cytoplasmic and molecule mobilization and spatial organization are possibly driven by the photons in thermal infrared (IR) radiation and generation of exclusion zone (EZ) water in the cytoplasm.

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: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.042
GPT teacher head0.374
Teacher spread0.333 · 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