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Record W2094798108 · doi:10.1007/s11910-011-0182-2

Modeling Neurodegeneration in Zebrafish

2011· review· en· W2094798108 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Neurology and Neuroscience Reports · 2011
Typereview
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsZebrafishDanioNeurodegenerationBiologyNeuroscienceModel organismVertebrateComputational biologyGeneDiseaseMedicinePathologyGenetics

Abstract

fetched live from OpenAlex

The zebrafish, Danio rerio, has been established as an excellent vertebrate model for the study of developmental biology and gene function. It also has proven to be a valuable model to study human diseases. Here, we reviewed recent publications using zebrafish to study the pathology of human neurodegenerative diseases including Parkinson's, Huntington's, and Alzheimer's. These studies indicate that zebrafish genes and their human homologues have conserved functions with respect to the etiology of neurodegenerative diseases. The characteristics of the zebrafish and the experimental approaches to which it is amenable make this species a useful complement to other animal models for the study of pathologic mechanisms of neurodegenerative diseases and for the screening of compounds with therapeutic potential.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.163
GPT teacher head0.348
Teacher spread0.184 · 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