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Record W2111468080 · doi:10.1242/dmm.002451

Mouse models of Huntington disease: variations on a theme

2009· article· en· W2111468080 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDisease Models & Mechanisms · 2009
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsHuntington's diseaseHuntingtinPhenotypeBiologyHuntingtin ProteinDiseaseGenetically modified mouseContext (archaeology)Translation (biology)Human diseaseGeneGeneticsNeuroscienceTransgeneMutantComputational biologyMessenger RNAMedicinePathology

Abstract

fetched live from OpenAlex

An accepted prerequisite for clinical trials of a compound in humans is the successful alleviation of the disease in animal models. For some diseases, however, successful translation of drug effects from mouse models to the bedside has been limited. One question is whether the current models accurately reproduce the human disease. Here, we examine the mouse models that are available for therapeutic testing in Huntington disease (HD), a late-onset neurodegenerative disorder for which there is no effective treatment. The current mouse models show different degrees of similarity to the human condition. Significant phenotypic differences are seen in mouse models that express either truncated or full-length human, or full-length mouse, mutant huntingtin (mHTT). These differences in phenotypic expression may be attributable to the influences of protein context, mouse strain and a difference in regulatory sequences between the mouse Htt and human HTT genes.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.043
GPT teacher head0.265
Teacher spread0.221 · 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