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Record W2102879385 · doi:10.1200/jco.2009.26.1917

Translating Gene Expression Into Clinical Care: Sarcomas As a Paradigm

2010· article· en· W2102879385 on OpenAlexaff
Torsten O. Nielsen, Robert B. West

Bibliographic record

VenueJournal of Clinical Oncology · 2010
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineCarcinogenesisGene expression profilingCancer researchEpigeneticsSarcomaDermatofibrosarcoma protuberansBioinformaticsComputational biologyGeneBiologyCancerGene expressionPathologyGeneticsInternal medicine

Abstract

fetched live from OpenAlex

Whereas most solid tumors are characterized by considerable genetic instability and molecular heterogeneity, sarcomas include many subtypes with very specific underlying molecular events driving oncogenesis. Gene expression profiling and other modern techniques have consequently had particular success in identifying the critical biologic pathways active in specific sarcomas, yielding insights which can be translated into useful diagnostic biomarkers. Public availability of data sets and new sequencing-based technologies will accelerate this process. Molecular studies have also identified oncogenic pathways of particular importance in sarcomas which can be targeted by investigational drugs. Examples include histone deacetylases in translocation-associated sarcomas of young adults, Akt/mammalian target of rapamycin in pleomorphic sarcomas, and macrophage colony-stimulating factor in tenosynovial giant cell tumor. Despite challenges in organization and accrual, future clinical trials of sarcomas need to be designed that take into account specific molecular subtypes as distinct diseases.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.123
GPT teacher head0.502
Teacher spread0.380 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2010
Admission routes1
Has abstractyes

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