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Record W2006860521 · doi:10.1159/000132162

Cystic fibrosis: progress in mapping the disease locus using polymorphic DNA markers. I.

2008· article· en· W2006860521 on OpenAlexaffabout
L.-C. Tsui, M. Zsiga, Derek Kennedy, N. Plavsic, D. Markiewicz, Manuel Buchwald

Bibliographic record

VenueCytogenetics and Cell Genetics · 2008
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedical geneticsSick childMedicineGeneticsFamily medicinePediatricsBiology

Abstract

fetched live from OpenAlex

The conventional approach to the identification of the affected gene in inherited diseases is through the demonstration of specific biochemical abnormalities in patients, their tissues, or cells. This approach has, unfortunately, been unsuccessful in the case of cystic fibrosis (CF), the most common severe autosomal recessive disorder in Causasians. An alternative approach is to locate the CF gene by linkage studies with chromosomal markers. We report here our results of testing 39 DNA restriction fragment length polymorphic (RFLP) markers using a panel of 45 two-generation Canadian families each with two or more affected children. The probability of linkage between each marker and CF was analyzed by the lod score method using the LIPED program. The results of these analyses show that none of the markers tested is closely linked to the disease locus.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.218
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.273
Teacher spread0.235 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations7
Published2008
Admission routes2
Has abstractyes

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