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Use of Random Amplified Polymorphic DNA (RAPD) Analysis for the Identification of <i>Giardia intestinalis</i> Subtypes and Phylogenetic Tree Construction

2003· article· en· W2018128251 on OpenAlexfundno aff
JITKA ŠEDINOVÁ, Jaroslav Flegr, Peter L. Ey, Jaroslav Kulda

Bibliographic record

VenueJournal of Eukaryotic Microbiology · 2003
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsRAPDBiologyPhylogenetic treeCladeGenotypeGeneticsPolymerase chain reactionGenetic markerDNAGiardiaGenetic variabilityPhylogeneticsGeneGenetic diversityPopulation

Abstract

fetched live from OpenAlex

A comparison of random amplified polymorphic DNA (RAPD) was used to investigate genetic polymorphisms among 25 isolates of Giardia intestinalis and to assess the utility of RAPD for subtype detection and genealogical analysis. Using data obtained for six human and 19 animal-derived isolates in polymerase chain reactions using 13 different primers, phylogenetic trees were constructed and bootstrap values computed by the program FreeTree. Three major clades were distinguished, corresponding to previously defined genetic assemblages A, B, and E. The purported specificity of assemblage E genotypes for artiodactyl hosts was supported. Assemblages A and B showed wide host spectra, including human and animal hosts. No correlation was found between the genotype of analyzed isolates and the presence or absence of the double-stranded RNA Giardiavirus. The results indicate that RAPD data provide reliable genetic information that can be used for both "fingerprinting" and genealogical purposes.

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)0.001
metaresearch head score (Gemma)0.004
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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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
GenreMethods

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

Citations26
Published2003
Admission routes1
Has abstractyes

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