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Record W2295672901 · doi:10.1016/s1470-2045(15)00581-1

Prognostic value of medulloblastoma extent of resection after accounting for molecular subgroup: a retrospective integrated clinical and molecular analysis

2016· article· en· W2295672901 on OpenAlexafffund
Eric M. Thompson, Thomas Hielscher, Éric Bouffet, Marc Remke, Betty Luu, Sridharan Gururangan, Roger E. McLendon, Darell D. Bigner, Eric Lipp, Sébastien Perreault, Yoon-Jae Cho, Gerald A. Grant, Seung‐Ki Kim, Ji Yeoun Lee, Amulya A. Nageswara Rao, Caterina Giannini, Kay Ka Wai Li, Ho‐Keung Ng, Yu Yao, Toshihiro Kumabe, Teiji Tominaga, Wiesława Grajkowska, Marta Perek‐Polnik, David C.Y. Low, Wan Tew Seow, Kenneth Tou En Chang, Jaume Mora, Ian F. Pollack, Ronald L. Hamilton, Sarah Leary, Andrew S. Moore, Wendy J. Ingram, Andrew R. Hallahan, Anne Jouvet, Michelle Fèvre‐Montange, Alexandre Vasiljevic, Cécile Faure‐Conter, Tomoko Shofuda, Naoki Kagawa, Naoya Hashimoto, Nada Jabado, Alexander G. Weil, Tenzin Gayden, Takafumi Wataya, Tarek Shalaby, Michael A. Grotzer, Karel Zitterbart, Jaroslav Štěrba, Leoš Křen, Tibor Hortobágyi, Álmos Klekner, László Bognár, Tímea Pócza, Péter Hauser, Ulrich Schüller, Shin Jung, Woo‐Youl Jang, Pim J. French, Johan M. Kros, Marie‐Lise C. van Veelen, Luca Massimi, Jeffrey R. Leonard, Joshua B. Rubin, Rajeev Vibhakar, Lola B. Chambless, Michael K. Cooper, Reid C. Thompson, Cláudia C. Faria, Alice Carvalho, Sofia Nunes, José Pimentel, Xing Fan, Karin M. Muraszko, Enrique López‐Aguilar, David Lyden, Livia Garzia, David Shih, Noriyuki Kijima, Christian Schneider, Jennifer Adamski, Paul A. Northcott, Marcel Kool, David Jones, Jennifer A. Chan, Ana Nikolić, Maria Luisa Garrè, Erwin G. Van Meir, Satoru Osuka, Jeffrey J. Olson, Arman Jahangiri, Brandyn Castro, Nalin Gupta, William A. Weiss, Iska Moxon‐Emre, Donald Mabbott, Álvaro Lassaletta, Cynthia Hawkins, Uri Tabori, James M. Drake, Abhaya V. Kulkarni, Peter B. Dirks, James T. Rutka, Andrey Korshunov, Stefan M. Pfister, Roger J. Packer, Vijay Ramaswamy, Michael D. Taylor

Bibliographic record

VenueThe Lancet Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationUniversity of TorontoUniversity of CalgaryMcGill UniversityCentre Hospitalier Universitaire Sainte-JustineHospital for Sick Children
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of HealthDeutsche KinderkrebsstiftungHospital for Sick ChildrenBrain Tumour Foundation of CanadaSt. Baldrick's FoundationDr. Mildred Scheel Stiftung für KrebsforschungNational Cancer InstituteUniversity of TorontoCanadian Institutes of Health ResearchPediatric Brain Tumor FoundationTerry Fox Research InstituteMagyar Tudományos AkadémiaAlex's Lemonade Stand Foundation for Childhood CancerMerckCURE Childhood CancerAmerican Cancer Society
KeywordsMedulloblastomaMedicineSubgroup analysisRadiation therapyOncologyChemoradiotherapyInternal medicineRetrospective cohort studySurgeryConfidence intervalPathology

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.349
Teacher spread0.326 · 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 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

Citations369
Published2016
Admission routes2
Has abstractno

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