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Record W2118783447 · doi:10.1093/annonc/mdu526

EURAMOS-1, an international randomised study for osteosarcoma: results from pre-randomisation treatment

2014· article· en· W2118783447 on OpenAlexaff
Jeremy Whelan, Stefan Bielack, Neyssa Marina, Sigbjørn Smeland, Gordana Jovic, Jane Hook, Mark Krailo, Jakob Anninga, Trude Butterfaß‐Bahloul, Tom Böhling, Gabriele Calaminus, Michael Capra, Claudia Deffenbaugh, Catharina Dhooge, Mikael Eriksson, Adrienne M. Flanagan, Hans Gelderblom, Allen M. Goorin, Richard Görlick, Georg Gosheger, R. J. Grimer, Kirsten Sundby Hall, K. Helmke, Pancras C.W. Hogendoorn, Gernot Jundt, Leo Kager, Thomas Kuehne, Ching C. Lau, G. Douglas Letson, James S. Meyer, Paul A. Meyers, Carol D. Morris, Hubert Mottl, Helen Nadel, Rajaram Nagarajan, R. Lor Randall, Paula J. Schomberg, R. Schwarz, Lisa A. Teot, Matthew R. Sydes, Mark L. Bernstein, James D. Pickering, Nicola Joffe, Matthias Kevric, Benjamin Sorg, Doojduen Villaluna, Caroline Wang, Martha Perisoglou, Leonardo Trani, Jenny Potratz, D. Carrle, Miriam Wilhelm, Katja Zils, C. Teske

Bibliographic record

VenueAnnals of Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsDalhousie UniversityBC Children's HospitalUniversity of British Columbia
FundersNational Cancer InstituteMedical Research Council
KeywordsMedicineOsteosarcomaIfosfamideEtoposideChemotherapyRegimenNeutropeniaSurgeryInternal medicineChemotherapy regimenPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0170.002

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 head0.116
GPT teacher head0.423
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations333
Published2014
Admission routes1
Has abstractno

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