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Record W2145493414 · doi:10.1309/mnpf3xxxvax5nm9h

A Multicenter Trial of the Effectiveness of ζ-Globin Enzyme-Linked Immunosorbent Assay and Hemoglobin H Inclusion Body Screening for the Detection of α<sup>0</sup>-Thalassemia Trait

2008· article· en· W2145493414 on OpenAlexaff
John Lafferty, David Barth, B. Sheridan, Andrew McFarlane, Linda M. Halchuk, Anne Raby, Mark Crowther

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2008
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsSt. Joseph's HospitalUniversity of TorontoMcMaster UniversityHamilton Regional Laboratory Medicine Program
Fundersnot available
KeywordsThalassemiaGlobinHemoglobinSickle cell traitTraitMedicineEnzymeBiologyInternal medicineBiochemistryDisease

Abstract

fetched live from OpenAlex

Routine laboratories use a hemoglobin H (HbH) screen to detect alpha-thalassemia carriers of fatal hemoglobin Bart's hydrops fetalis. This test is laborious and has sensitivity concerns. A commercial zeta-globin enzyme-linked immunosorbent assay (ELISA) is effective in detecting Southeast Asian (SEA) alpha-thalassemia. We present results of a study of the effectiveness of carrier detection of ELISA and a shortened HbH screen compared with gap polymerase chain reaction. ELISA was superior to the HbH screen for the SEA alpha0-thalassemia trait. The ELISA and H screen were equal for detection of all carriers encountered and combined were more effective than either test alone. A positive zeta-globin ELISA result is diagnostic of SEA alpha-thalassemia, and routine use of the zeta-globin ELISA in combination with a shortened HbH screen will improve the efficacy of prenatal screening for carriers of hemoglobin Bart's hydrops fetalis through improved detection and referral for follow-up DNA testing.

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)0.006
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.023
GPT teacher head0.331
Teacher spread0.308 · 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

Citations19
Published2008
Admission routes1
Has abstractyes

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