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Record W2054023787 · doi:10.2741/2225

Gene expression profiling of early involuting mammary gland reveals novel genes potentially relevant to human breast cancer

2006· article· en· W2054023787 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

VenueFrontiers in bioscience · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsInvolution (esoterism)Mammary glandBreast cancerGene expression profilingGeneCarcinogenesisBiologyMicroarray analysis techniquesGene expressionCancer researchCancerGeneticsNeuroscience

Abstract

fetched live from OpenAlex

Mammary gland involution represents one of the most dramatic examples of programmed cell death/apoptosis and tissue regression during development, yet large gaps still exist in the understanding of the mechanisms involved, and the key factors that trigger involution, are not yet identified. With the focus on identifying "novel" genes associated with mammary gland regression, we used microarray analysis to examine differentially expressed genes during early mammary gland involution in the mouse. We then examined the relevance of candidate genes to human tumorigenesis and identified a number of genes not previously implicated or not well characterized in human breast cancer. The expression levels of these genes in human breast cancer were confirmed in breast cancer cell lines and breast tumor tissues. This pilot study demonstrates proof of principle that through the analysis of gene expression during mammary gland involution, it may be possible to identify "novel" genes relevant human breast cancer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.464

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 science0.0000.000
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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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