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Record W2325704466 · doi:10.1530/erc-14-0232

The kinome associated with estrogen receptor-positive status in human breast cancer

2014· review· en· W2325704466 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

VenueEndocrine Related Cancer · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchCure Brain Cancer Foundation
KeywordsKinomeBreast cancerKinaseEstrogen receptorBioinformaticsComputational biologyEstrogen receptor alphaBiologyCancer researchMedicineCancerOncologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Estrogen receptor alpha (ERα) regulates and is regulated by kinases involved in several functions associated with the hallmarks of cancer. The following literature review strongly suggests that distinct kinomes exist for ERα-positive and -negative human breast cancers. Importantly, consistent with the known heterogeneity of ERα-positive cancers, different subgroups exist, which can be defined by different kinome signatures, which in turn are correlated with clinical outcome. Strong evidence supports the interplay of kinase networks, suggesting that targeting a single node may not be sufficient to inhibit the network. Therefore, identifying the important hubs/nodes associated with each clinically relevant kinome in ER+ tumors could offer the ability to implement the best therapy options at diagnosis, either endocrine therapy alone or together with other targeted therapies, for improved overall outcome.

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 score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.299
Teacher spread0.291 · 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