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Record W1987920499 · doi:10.2174/138161207782341268

Novel Pharmaceutical Approaches for Treating Patients with Cystic Fibrosis

2007· review· en· W1987920499 on OpenAlexaff
Z. Saeed, Gabriella Wojewodka, Didier Marion, Claudine Guilbault, Danuta Radzioch

Bibliographic record

VenueCurrent Pharmaceutical Design · 2007
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsCystic fibrosisMedicineMalabsorptionDiseaseClinical trialIntensive care medicineLung diseasePancreatic diseaseLungBioinformaticsInternal medicinePancreasBiology

Abstract

fetched live from OpenAlex

Before the cloning of the CFTR gene in 1989, there were relatively few treatment options for the many phenotypes associated with cystic fibrosis (CF). The advancement of research in areas such as immunology, molecular biology and pharmacology have provided new insights into the mechanism and evolution of CF. More than 40 systematic clinical trials evaluating new therapies for CF are presently registered with the NIH. A great deal of effort is focused on the main cause of mortality: chronic and persistent lung infections. Intestinal malabsorption, pancreatic insufficiency, reduced bone mineral density and reproductive abnormalities are other manifestations of this disease that have been targeted by innovated treatments which are giving renewed hope to CF patients and their families. The following review is a summary of the novel pharmaceutical approaches for the treatment of cystic fibrosis aimed at improving both the quality and the longevity of the lives of patients afflicted with this devastating disease.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.375
GPT teacher head0.484
Teacher spread0.108 · 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 designNot applicable
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

Citations12
Published2007
Admission routes1
Has abstractyes

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