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Record W2998094314 · doi:10.1080/23766808.2019.1706387

A cost-effective protocol for total DNA isolation from animal tissue

2019· article· en· W2998094314 on OpenAlexaff
Nicolás Peñafiel, Diana Flores, Juan Rivero de Aguilar, Juan M. Guayasamin, Elisa Bonaccorso

Bibliographic record

VenueNeotropical Biodiversity · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDNA extractionIsolation (microbiology)BiologyProtocol (science)Polymerase chain reactionDNAComputational biologyBioinformaticsGeneMedicinePathologyGenetics

Abstract

fetched live from OpenAlex

Laboratories that perform PCR on a routine basis need to count on reliable DNA isolation methods. In locations where supply of DNA extraction kits depends on importation, having an in-house protocol is desirable. This is also important for laboratories limited by budget constraints. We present a low-cost DNA isolation protocol that incorporates well-known techniques, but that we have adapted to various animal tissues. We tested this protocol on animal blood and muscle, and on cell suspension from skin swabs. The results were comparable, in terms of amount and quality of DNA, to those obtained with two other commercially available methods. DNA retrieved with this protocol has been successfully employed for Sanger sequencing of gene PCR products from animal tissues and blood, as well as for PCR-based diagnosis of chytrid fungus in amphibians and blood parasites in birds.

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)0.003
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: Protocol · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0220.042

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 head0.020
GPT teacher head0.276
Teacher spread0.256 · 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
GenreProtocol

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

Citations31
Published2019
Admission routes1
Has abstractyes

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