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Record W2209700710 · doi:10.1016/j.molonc.2015.12.007

Excellent translational research in oncology: A journey towards novel and more effective anti‐cancer therapies

2015· review· en· W2209700710 on OpenAlexaff
Abinaya Rajan, Anton Berns, Ulrik Ringborg, Julio E. Celis, B. A. J. Ponder, Carlos Caldas, David M. Livingston, Robert G. Bristow, Toby T. Hecht, Thomas Tursz, Henri G.A.M. van Luenen, Petri Bono, Tuula Helander, Kenneth B. Seamon, J.F. Smyth, Daniel Louvard, Alexander Eggermont, W.H. van Harten

Bibliographic record

VenueMolecular Oncology · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsPrincess Margaret Cancer Centre
FundersMedical Research CouncilEuropean CommissionNational Institute for Health and Care ResearchCancer Research UKAcademy of Medical SciencesHelsingin ja Uudenmaan Sairaanhoitopiiri
KeywordsExcellenceBench to bedsideTranslational researchMedicineCancerOncologyAlternative medicineInternal medicineMedical physicsPolitical sciencePathology

Abstract

fetched live from OpenAlex

Comprehensive Cancer Centres (CCCs) serve as critical drivers for improving cancer survival. In Europe, we have developed an Excellence Designation System (EDS) consisting of criteria to assess "excellence" of CCCs in translational research (bench to bedside and back), with the expectation that many European CCCs will aspire to this status.

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)0.001
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 score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.119
GPT teacher head0.470
Teacher spread0.352 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations12
Published2015
Admission routes1
Has abstractyes

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