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Cell shape, division and development: the 2002 American Society for Microbiology (ASM) conference on prokaryotic development

2003· article· en· W2146496228 on OpenAlexfundno aff
Rainer M. Figge, James W. Gober

Bibliographic record

VenueMolecular Microbiology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Science FoundationNational Institutes of HealthUppsala UniversitetMcMaster UniversityU.S. Department of Energy
KeywordsCaulobacter crescentusBiologyMyxococcus xanthusMulticellular organismBacillus subtilisCell divisionBacterial cell structureComputational biologyCell biologyMicrobiologyCell cycleCellGeneticsBacteriaGene

Abstract

fetched live from OpenAlex

In the last decade, the use of cytological techniques, together with the analysis of complete genomes, has dramatically advanced our understanding of bacterial development. Work on several well-developed model systems such as Bacillus subtilis, Caulobacter crescentus, Myxococcus xanthus and Streptomyces spp., has provided us with an in-depth understanding of processes such as sporulation, multicellular behaviour and the bacterial cell cycle. At the same time, these studies have revolutionized our view of the bacterial cell and shown it to be a highly complex entity with spatial and temporal organization. The recent American Society for Microbiology (ASM) conference on prokaryotic development demonstrated that several laboratories have now started to connect data obtained through functional genomic analysis with subcellular organization, thereby generating three-dimensional regulatory networks. This meeting report highlights new findings in the field, such as regulation of protein localization during sporulation and the cell cycle, control of cell-cell interaction and the initiation of cell division.

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.

How this classification was reachedexpand

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2003
Admission routes1
Has abstractyes

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