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Record W2615290191 · doi:10.1111/1556-4029.13551

Evaluation of a Freezer Mill for Bone Pulverization prior to <scp>DNA</scp> Extraction: An Improved Workflow for <scp>STR</scp> Analysis

2017· article· en· W2615290191 on OpenAlexaff
Emely Morales Colón, Mireya Hernández, Mariel Candelario, María Meléndez, Tracey Dawson Cruz

Bibliographic record

VenueJournal of Forensic Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsDawson College
Fundersnot available
KeywordsExtraction (chemistry)DNA extractionGrindingSTR analysisMillMaterials scienceReuseDNAPulp and paper industryChromatographyEnvironmental sciencePolymerase chain reactionComposite materialChemistryMicrosatelliteWaste managementAlleleEngineeringMechanical engineeringBiochemistry

Abstract

fetched live from OpenAlex

Traditional methods for bone pulverization typically generate heat, risking stability of DNA sample. SPEX™ has developed cryogenic grinders which introduce liquid nitrogen to cool the sample and aid in the grinding process. In this study, the Freezer Mill 6970 EFM was used with two DNA extraction methods and routine downstream STR analysis procedures. DNA from as little as 0.1 g of bone powder was used to develop full STR profiles after freezer mill pulverization, and the method was reproducible. Further, no contamination was detected upon cleaning/reuse of the sample vials. There were no significant differences in DNA yield, STR alleles detected, or peak heights using the freezer mill as compared to traditional grinding, and successful DNA profiles were achieved from as low as 0.1 g of bone powder with this method. Overall, this work indicates that this cryogenic mill method may be used as a viable alternative to traditional tissue grinders.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.117
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.366
Teacher spread0.327 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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