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Record W2136301442 · doi:10.1017/thg.2012.122

The Vietnam Era Twin Registry: A Quarter Century of Progress

2012· article· en· W2136301442 on OpenAlexaboutno aff
Melyssa Tsai, Alaina Mori, Christopher W. Forsberg, Nicole Waiss, Jennifer L. Sporleder, Nicholas L. Smith, Jack Goldberg

Bibliographic record

VenueTwin Research and Human Genetics · 2012
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Heart, Lung, and Blood InstituteNational Institute on Alcohol Abuse and AlcoholismNational Institute on AgingNational Institute of Mental HealthU.S. Department of Veterans Affairs
KeywordsQuarter (Canadian coin)PopulationMedicineDemographyGeographyFamily medicineEnvironmental healthArchaeologySociology

Abstract

fetched live from OpenAlex

Now celebrating its 26th year of existence, the Vietnam Era Twin Registry continues to be one of the largest national samples of adult twins in the United States. The Registry twin member population is composed of 7,369 US male-male twin pair Veterans (14,738 total individuals) who served on active duty in the military during the Vietnam conflict (1964-1975). The Registry also maintains a register, data repository, and a biospecimen repository. Details on the operations of the Registry are described, as well as an overview of specific studies. Registry maintenance activities are also described, including the updating of contact information and vital status. Future plans include expanding the biospecimen repository and obtaining input from twins about study methods and diseases and conditions they would like to see investigated.

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)0.117
metaresearch head score (Gemma)0.165
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: none
Teacher disagreement score0.117
Threshold uncertainty score0.618

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1170.165
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.013
Science and technology studies0.0020.004
Scholarly communication0.0070.015
Open science0.0040.008
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0070.002

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 head0.079
GPT teacher head0.402
Teacher spread0.323 · 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

Citations37
Published2012
Admission routes1
Has abstractyes

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