MétaCan
Menu
Back to cohort
Record W4381414128 · doi:10.21769/bioprotoc.4704

Triplet-primed PCR and Melting Curve Analysis for Rapid Molecular Screening of Spinocerebellar Ataxia Types 1, 2, and 3

2023· article· en· W4381414128 on OpenAlexaff
Mulias Lian, Mingjue Zhao, Gui-Ping Phang, Indhu‐Shree Rajan‐Babu, Samuel S. Chong

Bibliographic record

VenueBIO-PROTOCOL · 2023
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsBC Children's HospitalChildren's & Women's Health Centre of British Columbia
Fundersnot available
KeywordsSpinocerebellar ataxiaCapillary electrophoresisTrinucleotide repeat expansionMelting curve analysisBiologyMolecular biologyMicrosatelliteTandem repeatGeneticsGenotypeGenePolymerase chain reactionAllele

Abstract

fetched live from OpenAlex

loci using melting curve analysis of triplet-primed PCR products. Each of the three separate assays employs a plasmid DNA carrying a known repeat size to generate a threshold melt peak temperature, which effectively distinguishes expansion-positive samples from those without a repeat expansion. Samples that are screened positive based on their melt peak profiles are subjected to capillary electrophoresis for repeat sizing and genotype confirmation. These screening assays are robust and provide accurate detection of the repeat expansion while eliminating the need for fluorescent PCR and capillary electrophoresis for every sample.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.337
Teacher spread0.271 · 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 teacher head, 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBIO-PROTOCOLSame topicGenetic Neurodegenerative DiseasesFrench-language works237,207