MétaCan
Menu
Back to cohort
Record W4411849053 · doi:10.1016/j.fsisyn.2025.100593

National Technology Validation and Implementation Collaborative (NTVIC): Updated guidelines for establishing Forensic Investigative Genetic Genealogy (FIGG) programs

2025· editorial· en· W4411849053 on OpenAlexaff
Ray Wickenheiser, Jennifer E. Naugle, Brian A. Hoey, Rylene Nowlin, Claire L. Glynn, Raymond Valerio, Lance Allen, Stephanie Stoiloff, Jennifer Kochanski, Dixie Peters, Rachel H. Oefelein, Rockne Harmon, Barbara Llewellyn, Trisha Kacer, Paul Panther, Colleen Fitzpatrick, Garry Bombard, Alison Sears, David Mittelman, Stephanie M. Fullerton, Jessica Koong, M J Chambers, Melisa Wittkowske, Ken Carrierre, Nichole Schwedelsky, Ted Liomanis, Michael A. Kelly, Stephen Smith, Jonathan Nauman, Tom Cober

Bibliographic record

VenueForensic Science International Synergy · 2025
Typeeditorial
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMontreal Police ServiceBoise Cascade (Canada)
Fundersnot available
KeywordsForensic scienceForensic geneticsGenealogyData scienceComputer scienceHistoryArchaeologyGeneticsBiologyMicrosatellite

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.078
metaresearch head score (Gemma)0.211
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.078
Threshold uncertainty score0.415

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.211
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0090.005
Science and technology studies0.0060.006
Scholarly communication0.0140.007
Open science0.0100.004
Research integrity0.0450.046
Insufficient payload (model declined to judge)0.0090.010

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 head0.178
GPT teacher head0.539
Teacher spread0.361 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations2
Published2025
Admission routes1
Has abstractno

Explore more

Same venueForensic Science International SynergySame topicEthics in Clinical ResearchFrench-language works237,207