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Record W2744510683 · doi:10.1101/cshperspect.a029348

Connexins and Disease

2017· review· en· W2744510683 on OpenAlexaff
Mario Delmar, Dale W. Laird, Christian C. Naus, Morten Schak Nielsen, Vytautas K. Verselis, Thomas W. White

Bibliographic record

VenueCold Spring Harbor Perspectives in Biology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsUniversity of British ColumbiaWestern University
FundersNational Eye Institute
KeywordsBiologyDiseaseComputational biologyEvolutionary biologyInternal medicine

Abstract

fetched live from OpenAlex

Inherited or acquired alterations in the structure and function of connexin proteins have long been associated with disease. In the present work, we review current knowledge on the role of connexins in diseases associated with the heart, nervous system, cochlea, and skin, as well as cancer and pleiotropic syndromes such as oculodentodigital dysplasia (ODDD). Although incomplete by virtue of space and the extent of the topic, this review emphasizes the fact that connexin function is not only associated with gap junction channel formation. As such, both canonical and noncanonical functions of connexins are fundamental components in the pathophysiology of multiple connexin related disorders, many of them highly debilitating and life threatening. Improved understanding of connexin biology has the potential to advance our understanding of mechanisms, diagnosis, and treatment of 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)0.001
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.004

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 head0.056
GPT teacher head0.371
Teacher spread0.315 · 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

Citations107
Published2017
Admission routes1
Has abstractyes

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