MétaCan
Menu
Back to cohort
Record W2004451473 · doi:10.2217/pgs.09.112

Mitochondrial Gene Profiling: Translational Perspectives

2009· review· en· W2004451473 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

VenuePharmacogenomics · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMitochondrial diseaseComputational biologyBiologyDiseaseGene expression profilingDNA microarrayBioinformaticsMicroarrayDrug developmentGeneMitochondrionMedicineMitochondrial DNADrugGeneticsGene expressionPharmacologyPathology

Abstract

fetched live from OpenAlex

The last decade has witnessed the development of multiple microarray platforms designed to study, in a comprehensive fashion, the expression and sequence of both mitochondrial and nuclear genes that encode mitochondrial proteins. Mitochondrial dysfunction has been implicated in a number of severe medical conditions including cancer, metabolic diseases (i.e., cardiovascular, diabetes and obesity) and neurodegenerative disorders and it is responsible for the adverse effects of numerous drugs. Profiling of the genetic and genomic status of mitochondria with focused microarrays offers the promise of rapidly and robustly identifying novel biomarkers for early disease diagnoses and prognoses, predicting of drug safety, liability, and selecting and stratifying of patients in clinical trials.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.047
GPT teacher head0.345
Teacher spread0.297 · 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