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Individuality in Bacteria

2008· review· en· W2149035803 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

VenueAnnual Review of Genetics · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiologyVariation (astronomy)Context (archaeology)Evolutionary biologyPhase variationDiversity (politics)Variety (cybernetics)Mechanism (biology)PopulationBacteriaEvolutionary ecologyEcologyGeneticsEpistemologyArtificial intelligenceComputer scienceSociologyPhenotypeDemographyHost (biology)

Abstract

fetched live from OpenAlex

While traditionally microbiologists have examined bacterial behavior averaged over large populations, increasingly we are becoming aware that bacterial populations can be composed of phenotypically diverse individuals generated by a variety of mechanisms. Though the results of different mechanisms, the phenomena of bistability, persistence, variation in chemotactic response, and phase and antigenic variation are all strategies to develop population-level diversity. The understanding of individuality in bacteria requires an appreciation of their environmental and ecological context, and thus evolutionary theory regarding adaptations to time-variable environments is becoming more applicable to these problems. In particular, the application of game and information theory to bacterial individuality has addressed some interesting problems of bacterial behavior. In this review we discuss the mechanisms of generating population-level variability, and the application of evolutionary theory to problems of individuality in bacteria.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.023
GPT teacher head0.354
Teacher spread0.331 · 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