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Record W2901308104 · doi:10.1007/s11060-018-03038-2

International experience in the development of patient-derived xenograft models of diffuse intrinsic pontine glioma

2018· article· en· W2901308104 on OpenAlexaff
Maria Tsoli, Han Shen, Chelsea Mayoh, Laura Franshaw, Anahid Ehteda, Dannielle Upton, Diana Carvalho, Maria Vinci, Michaël H. Meel, Dannis G. van Vuurden, Alexander Plessier, David Castel, Rachid Drissi, Michael Farrell, Jane Cryan, Darach Crimmins, John Caird, Jane Pears, Stephanie Francis, Louise Ludlow, Andrea Carai, Angela Mastronuzzi, Bing Liu, Jordan R. Hansford, Tim Hassall, Maria Kirby, Maryam Fouladi, Cynthia Hawkins, Michelle Monje, Jacques Grill, Chris Jones, Esther Hulleman, David S. Ziegler

Bibliographic record

VenueJournal of Neuro-Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick Children
FundersNational Institute for Health and Care ResearchCure Brain Cancer FoundationMedical Research CouncilChildren’s Hospital of Wisconsin Research InstituteCHILDREN with CANCER UKBrain Tumour CharityMurdoch Children's Research InstituteNational Health and Medical Research CouncilCancer Research UKRoyal Children's Hospital FoundationChildren's Hospital FoundationBrain Research UKCure Starts Now Foundation
KeywordsGliomaIn vitroIn vivoBiopsyMedicinePathologyCancer researchOncologyBiology

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)0.010
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.326
Teacher spread0.284 · 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 designBench or experimental
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

Citations39
Published2018
Admission routes1
Has abstractno

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