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Record W1999062693 · doi:10.1515/jpm-2012-0145

Preterm Birth Genome Project (PGP) – validation of resources for preterm birth genome-wide studies

2012· article· en· W1999062693 on OpenAlexaff
Craig E. Pennell, Felipe Vadillo‐Ortega, David M. Olson, Eun‐Hee Ha, Scott M. Williams, Timothy M. Frayling, Siobhan M. Dolan, Michael Katz, Mario Merialdi, Ramkumar Menon

Bibliographic record

VenueJournal of Perinatal Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of Alberta
FundersWorld Health OrganizationMarch of Dimes Foundation
KeywordsMedicineGenomeObstetricsNeonatologyPremature birthPregnancyGeneticsGestational ageGeneBiology

Abstract

fetched live from OpenAlex

We determined a series of quality control (QC) analyses to assess the usability of DNA collected and processed from different countries utilizing different DNA extraction techniques prior to genome-wide association studies (GWAS). The quality of DNA collected utilizing four different DNA extraction techniques and the impact of shipping DNA at different temperatures on array performance were evaluated. Fifteen maternal-fetal pairs were used from four countries. DNA was extracted using four approaches: whole blood, blood spots with whole genome amplification (WGA), saliva and buccal swab. Samples were sent to a genotyping facility, either on dry ice or at room temperature and genotyped using Affymetrix SNP array 6.0. QC measured included extraction techniques, effect of shipping temperatures, accuracy and Mendelian concordance. Significantly fewer (50 % ) single nucleotide polymorphisms (SNPs) passed QC metrics for buccal swab DNA (P < 0.0001) due to missing genotype data (P < 0.0001). Whole blood or saliva DNA had the highest call rates (99.2 0.4 % and 99.3 0.2 % , respectively) and Mendelian concordance. Shipment temperature had no effect. DNA from blood or saliva had the highest call rate accuracy, and buccal swabs had the lowest. DNA extracted from blood, saliva and blood spots were found suitable for GWAS in our study.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.413
Teacher spread0.313 · 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 designNot applicable
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

Citations11
Published2012
Admission routes1
Has abstractyes

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