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RealTimePCR-Protocol-miRNA-SCALONMC v1

2022· preprint· en· W4308603194 on OpenAlexaff
Marcela Scalon

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsTaqManmicroRNAReal-time polymerase chain reactionProtocol (science)Primer (cosmetics)Computational biologyBiologyMolecular biologyChemistryGeneticsMedicineGenePathology

Abstract

fetched live from OpenAlex

This protocol is intended as a guideline to perform the Real Time PCR (qPCR or rtPCR) procedure to detect and quantify miRNAs. This method use TaqMan® MicroRNA Assays and Applied Biosystems real-time PCR instruments. The assays are preformulated primer and probe sets designed to detect and quantify miRNAs, and can detect and quantify small RNA in 1 to 10 ng of total RNA with a dynamic range of greater than six logs. This protocol works on detecting miRNA from samples that were purified from plasma and serum. The amplified products of the RT procedure must be stored − 15 to − 25 °C, if not used immediately for rtPCR. The aim of this protocol is to use a sequence- specific TaqMan® assay to accurately detect miRNAs.

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)0.006
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: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0050.003
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0050.003
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0970.125

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 head0.017
GPT teacher head0.305
Teacher spread0.289 · 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
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

Citations0
Published2022
Admission routes1
Has abstractyes

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