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Record W4395053828 · doi:10.1016/j.fsigen.2024.103053

Ethical considerations for Forensic Genetic Frequency databases: First Report conception and development

2024· article· en· W4395053828 on OpenAlex

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

VenueForensic Science International Genetics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsMcGill UniversityMcGill University and Génome Québec Innovation Centre
Fundersnot available
KeywordsForensic scienceDatabaseEngineering ethicsComputer scienceData scienceBiologyEngineeringGenetics

Abstract

fetched live from OpenAlex

The Forensic Databases Advisory Board (FDAB), an independent board that assists the International Society for Forensic Genetics (ISFG), has presented a First Report on ethical aspects of the following Forensic Genetic Frequency Databases (FGFD): EMPOP, STRidER and YHRD. The FDAB designed an ethical framework to evaluate the content of these FGFD, and the factors to be considered for retention and acceptance of submissions. The FDAB framework proposes to categorize submissions according to the risk of having contravened the universal ethical principles outlined by international organizations, and the guidelines adopted by the ISFG. The report has been open to discussion by the scientific community since 2023. Herein we present the conception and development of the First Report along with a summary of its content, with consideration of the feedback received.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.056
GPT teacher head0.365
Teacher spread0.309 · 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