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Record W2158797036 · doi:10.1098/rstb.2007.2044

Antibiotics as signalling molecules

2007· review· en· W2158797036 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

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2007
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyGeneSignallingAntibioticsCell signalingSignalling pathwaysTranscription (linguistics)Transcription factorGene expressionSignal transductionMicrobiologyCell biologyBiochemistry

Abstract

fetched live from OpenAlex

We present the argument that the majority of low-molecular-weight organic compounds made and secreted by microbes play roles as cell-signalling molecules in the environment. Of the large number of compounds isolated to date, only a small fraction have been shown to possess useful therapeutic antibiotic activity. However, most microbial metabolites modulate gene transcription at low concentrations, and this is proposed to be the primary effect of the compounds in the maintenance of microbial communities in the environment. Thus, microbial metabolites constitute a large collection of cell-signalling molecules that regulate gene expression in microbial populations and possibly the interactions of these populations with the surrounding organisms.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
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 head0.131
GPT teacher head0.323
Teacher spread0.193 · 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