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Record W21134345

New Developments in Quantitative Real-time Polymerase Chain Reaction Technology.

2014· review· en· W21134345 on OpenAlexaff
Martin Filion

Bibliographic record

VenueCurrent Issues in Molecular Biology · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsReal-time polymerase chain reactionNucleic acidComputer scienceSoftwarePolymerase chain reactionComputational biologyBiochemical engineeringNanotechnologyBiologyEngineeringBiochemistryMaterials scienceOperating systemGene
DOInot available

Abstract

fetched live from OpenAlex

Real time-quantitative PCR (RT-qPCR) technology has revolutionized the detection landscape in every area of molecular biology. The fundamental basis of this technology has remained unchanged since its inception, however various modifications have enhanced the overall performance of this highly versatile technology. These improvements have ranged from changes in the individual components of the enzymatic reaction cocktail (polymerizing enzymes, reaction buffers, probes, etc.) to the detection system itself (instrumentation, software, etc.). The RT-qPCR technology currently available to researchers is more sensitive, faster and affordable than when this technology was first introduced. In this article, we summarize the developments of the last few years in RT-qPCR technology and nucleic acid amplification.

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.008

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 head0.404
Teacher spread0.382 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations41
Published2014
Admission routes1
Has abstractyes

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