MétaCan
Menu
Back to cohort
Record W2130032208 · doi:10.1039/c2ay05801d

Repeated capillary electrophoresis separations conducted on a commercial DNA chip

2012· article· en· W2130032208 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnalytical Methods · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCapillary electrophoresisChipSizingChromatographyLab-on-a-chipComputer scienceReproducibilitySample (material)VendorReagentCapillary actionProcess engineeringChemistryNanotechnologyMaterials scienceMicrofluidicsEngineeringTelecommunicationsBusiness

Abstract

fetched live from OpenAlex

Multi-sample microchip capillary electrophoresis separations of a DNA sample (i.e. pUC18 DNA Hae III restriction digest) have been conducted on a commercial bioanalyzer. According to the vendor's specifications, a new chip must be used and the gel–dye mix must be used within 2 weeks for the best possible results. However, such a requirement of new chips and fresh reagents is quite costly, especially during preliminary research work, or instructional experiments in teaching labs. Therefore, we have developed a method to clean the microchip, so that the same DNA chip can be inspected and re-used. Our experimental data show that the CE separations conducted on a new chip and on a cleaned chip are comparable without loss in sizing accuracy and reproducibility. The gel–dye mix can also be used many times, longer than 2 weeks as specified by the vendor until the gel–dye changes color. This method will provide cost-saving advantage to laboratories during training and preliminary research work.

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.

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)0.000
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 score0.122
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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