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Automated Processing of Forensic Casework Samples Using Robotic Workstations Equipped with Nondisposable Tips: Contamination Prevention

2008· article· en· W2057291521 on OpenAlexaff
Chantal J. Frégeau, C. Marc Lett, Jim Elliott, Craig Yensen, Ron M. Fourney

Bibliographic record

VenueJournal of Forensic Sciences · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsRoyal Canadian Mounted Police
Fundersnot available
KeywordsContaminationComputer scienceBleachProtocol (science)WorkstationPipetteSodium hypochloriteChemistryOperating systemMedicine

Abstract

fetched live from OpenAlex

An automated process has been developed for the analysis of forensic casework samples using TECAN Genesis RSP 150/8 or Freedom EVO liquid handling workstations equipped exclusively with nondisposable tips. Robot tip cleaning routines have been incorporated strategically within the DNA extraction process as well as at the end of each session. Alternative options were examined for cleaning the tips and different strategies were employed to verify cross-contamination. A 2% sodium hypochlorite wash (1/5th dilution of the 10.8% commercial bleach stock) proved to be the best overall approach for preventing cross-contamination of samples processed using our automated protocol. The bleach wash steps do not adversely impact the short tandem repeat (STR) profiles developed from DNA extracted robotically and allow for major cost savings through the implementation of fixed tips. We have demonstrated that robotic workstations equipped with fixed pipette tips can be used with confidence with properly designed tip washing routines to process casework samples using an adapted magnetic bead extraction protocol.

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)0.000
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 score0.097
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.041
GPT teacher head0.329
Teacher spread0.288 · 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

Citations51
Published2008
Admission routes1
Has abstractyes

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