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Record W3130118722 · doi:10.1007/s00401-021-02284-5

Clinical and molecular heterogeneity of pineal parenchymal tumors: a consensus study

2021· article· en· W3130118722 on OpenAlexafffund
Anthony P. Y. Liu, Bryan Li, Elke Pfaff, Brian Gudenas, Alexandre Vasiljevic, Brent A. Orr, Christelle Dufour, Matija Snuderl, Matthias A. Karajannis, Marc K. Rosenblum, Eugene Hwang, Ho‐Keung Ng, Jordan R. Hansford, Alexandru Szathmári, Cécile Faure‐Conter, Thomas E. Merchant, Max F. Levine, Nancy Bouvier, Katja von Hoff, Martin Mynarek, Stefan Rutkowski, Felix Sahm, Marcel Kool, Cynthia Hawkins, Arzu Onar‐Thomas, Giles Robinson, Amar Gajjar, Stefan M. Pfister, Éric Bouffet, Paul A. Northcott, David Jones, Annie Huang

Bibliographic record

VenueActa Neuropathologica · 2021
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersAmerican Lebanese Syrian Associated CharitiesCanadian Institutes of Health ResearchNational Cancer InstituteDeutsche KinderkrebsstiftungFriedberg Charitable FoundationDivision of Cancer Prevention, National Cancer Institute
KeywordsBiologymicroRNAParenchymaDNA methylationTranscriptomeCancer researchInternal medicineMethylationOncologyPathologyBioinformaticsGeneMedicineGene expressionGenetics

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)0.032
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0060.002
Research integrity0.0030.002
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 head0.051
GPT teacher head0.343
Teacher spread0.291 · 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 designQualitative
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

Citations86
Published2021
Admission routes2
Has abstractno

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