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Record W1989016882 · doi:10.1080/00450610902935999

DNA profiles from flip-open cell phones

2009· article· en· W1989016882 on OpenAlex
Meghan J. McFadden, Diana E. Friedland, Margaret M. Wallace

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

VenueAustralian Journal of Forensic Sciences · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMicrosatelliteSTR analysisPhoneBuccal swabSignificant differenceDNA profilingBiologyDNAAlleleGeneticsMedicineInternal medicineGene

Abstract

fetched live from OpenAlex

Flip-open style cell phones were investigated for the potential to produce quality genetic profiles that could be used in forensic casework. Swabs were taken of the outside/back and the inside ear speaker of ten flip-phones on two occasions – prior to and seven days after cleaning with 95% ethanol. Buccal swabs were collected as exemplars. The samples were amplified using the AmpFlSTR ProfilerPlus PCR Kit for 35 cycles and STR profiles were generated using an ABI Prism 310 Genetic Analyzer and GeneMapper ID analysis software v3.2. The phone profiles were compared to the references and to each other, to assess the quality of the profiles. The completeness of the profiles varied greatly, even within an experimental condition. There was no significant difference in the percentage correct alleles or in the number of drop-in alleles in the DNA profiles for the outside/inside locations or for the pre/post-cleaning times. The findings of this study demonstrate the need for collecting multiple samples from discrete locations on a cell phone if such evidence is encountered in forensic cases.

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 score0.027
Threshold uncertainty score0.309

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.316
Teacher spread0.289 · 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