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Record W2461474485 · doi:10.1007/978-1-60327-565-1_15

Isolation Independent Methods of Characterizing Phage Communities 1: Strain Typing Using Fingerprinting Methods

2009· article· en· W2461474485 on OpenAlexaff
Clemens Pausz, Jessica L. Clasen, Curtis A. Suttle

Bibliographic record

VenueMethods in molecular biology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPulsed-field gel electrophoresisBiologyGenomeIsolation (microbiology)Temperature gradient gel electrophoresisComputational biologyGenetic diversityGeneticsGeneMicrobiologyGenotypePopulation16S ribosomal RNA

Abstract

fetched live from OpenAlex

Since most of the phage genomes isolated from natural samples are previously unknown sequences, an isolation-independent approach is necessary to quantify the diversity of natural viral communities. Currently, two different methodological approaches are widely used to obtain genetic fingerprints of natural phage communities. While the separation of different viral genomes with pulsed field gel electrophoresis (PFGE) is based on the size of the genome, denaturing gradient gel electrophoresis (DGGE) uses minor differences in gene base composition to separate fragments of amplified DNA from natural viral communities. Finger printing techniques are a relatively fast and cheap tool to assess the diversity of environmental viruses. Together, PFGE and DGGE provide useful tools to study viral ecology in natural habitats.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.004

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 head0.050
GPT teacher head0.431
Teacher spread0.381 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2009
Admission routes1
Has abstractyes

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