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Validation of the DNA IQ™ System for use in the DNA Extraction of High Volume Forensic Casework

2004· article· en· W2048577436 on OpenAlexvenueno aff
Diane Komonski, A. Marignani, Melanie L. Richard, J.R.H. Frappier, James Newman

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsnot available
Fundersnot available
KeywordsDNA extractionChromatographyLysis bufferIncubationMicrosatelliteExtraction (chemistry)STR analysisDNALysisBiologyChemistryPolymerase chain reactionMolecular biologyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

A modified DNA IQ™ System (Promega) protocol was validated for the rapid processing of a range of samples, including cigarette butts, gum, dried nasal secretions on tissue, swabbed drink containers and blood samples. Promega's standard Database Protocol was primarily designed for DNA extraction from blood stains. Modifications to this protocol were required to increase extraction efficiency from a range of sample types. These included: decreasing the incubation temperature; replacing the initial incubation in the kit's lysis buffer with an extraction buffer containing proteinase K; using a 25 μL elution volume; decreasing the number of resin washes from 3 to 1. Complete 9-locus STR (short tandem repeat) profiles were generated in most instances without the need for additional sample purification prior to amplification. In addition to being a fast and effective method of DNA extraction, the use of a single protocol for a range of samples makes the procedure amenable to automation.

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)0.001
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 score0.044
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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

Citations12
Published2004
Admission routes1
Has abstractyes

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