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Record W964867498 · doi:10.1520/jfs15121j

NIST Mixed Stain Studies #1 and #2: Interlaboratory Comparison of DNA Quantification Practice and Short Tandem Repeat Multiplex Performance with Multiple-Source Samples

2001· article· en· W964867498 on OpenAlexaff
David L. Duewer, Margaret C. Kline, Janette W. Redman, Pamela J. Newall, Dennis J. Reeder

Bibliographic record

VenueJournal of Forensic Sciences · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsMultiplexMicrosatelliteDNA profilingStainDNA extractionSTR multiplex systemSTR analysisTypingForensic identificationDNAComputational biologyChromatographyMultiplex polymerase chain reactionBiologyPolymerase chain reactionChemistryGeneticsStaining

Abstract

fetched live from OpenAlex

The Mixed Stain Study 1 (MSS1, Apr.-Nov. 1997) and Mixed Stain Study 2 (MSS2, Jan.-May 1999) evaluated multiplexed short-tandem repeat (STR) DNA typing systems with samples containing DNA from more than one source. These interlaboratory challenge studies evaluated forensic STR measurement, interpretation, and reporting practice using well-characterized samples of very different analytical difficulty. None of the relatively few errors reported in either exercise resulted in a false identification of a reference source; several errors in evaluating the unknown source in three-source samples would hinder matching the profile in any archival database. None of the measurement anomalies reported is associated with any particular STR multiplex; all DNA amplification anomalies are associated with inefficient DNA extraction, inaccurate DNA quantitation, and/or analytical threshold policies.

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)0.016
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.064
GPT teacher head0.365
Teacher spread0.300 · 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 designObservational
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

Citations34
Published2001
Admission routes1
Has abstractyes

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