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Record W3128361515 · doi:10.5858/2001-125-0081-cgh

Comparative Genomic Hybridization

2001· article· en· W3128361515 on OpenAlexaff
Irene Barrett, Brenda Lomax, Tatiana Loukianova, Steven Tang, Valia S. Lestou, Dagmar K. Kalousek

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsComparative genomic hybridizationAneuploidyBiologyAmniotic fluidCytogeneticsAbortionFetusAndrologyIn situ hybridizationPathologyPregnancyObstetricsGenomeGeneticsMedicineChromosomeGene

Abstract

fetched live from OpenAlex

OBJECTIVE: To demonstrate the effectiveness of comparative genomic hybridization (CGH) for analysis of reproductive pathology specimens in clinical cytogenetics laboratories. DESIGN: A total of 856 CGH analyses were performed on various placental and fetal tissues derived from 368 specimens of spontaneous abortions and on placentas from 219 pregnancies with live-born infants. The live-born infants were clinically evaluated as normally developed, with either a normal birth weight or with intrauterine growth restriction; some live-born infants had an abnormal prenatal triple screen with normal cytogenetic results on amniotic fluid cell cultures. RESULTS: Comparative genomic hybridization analysis was successfully performed on 856 samples from spontaneously aborted specimens and term placentas. Failure of analysis occurred in 1.6% of samples and was due to an insufficient amount of tissue for DNA extraction. Comparative genomic hybridization identified aneuploidy in 53% of spontaneous abortion samples and 3.1% of term placentas. CONCLUSIONS: Comparative genomic hybridization analysis is a useful clinical tool for detection of aneuploidy in placental and fetal tissues. It provides a genome-wide screen while eliminating tissue culture failures, culture artifacts, and maternal cell contamination. We present practical guidelines for interpreting CGH profiles derived from human reproductive specimens.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.024
GPT teacher head0.301
Teacher spread0.277 · 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 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

Citations31
Published2001
Admission routes1
Has abstractyes

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