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Record W1961162667 · doi:10.1002/pbc.25313

SIOP PODC adapted treatment recommendations for standard-risk medulloblastoma in low and middle income settings

2014· article· en· W1961162667 on OpenAlexaff
Jeannette Parkes, Marc Hendricks, Peter Ssenyonga, John Mugamba, Elizabeth Molyneux, Antoinette Schouten‐van Meeteren, Ibrahim Qaddoumi, Graham Fieggen, Sandra Luna‐Fineman, Scott C. Howard, Dipayan Mitra, Éric Bouffet, Alan Davidson, Simon Bailey

Bibliographic record

VenuePediatric Blood & Cancer · 2014
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersBrain Tumour CharityCancer Research UK
KeywordsMedulloblastomaMedicineBlood cancerLow and middle income countriesRadiation therapyIntensive care medicineCancerDeveloping countrySurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

Effective treatment of children with medulloblastoma requires a functioning multi-disciplinary team with adequate neurosurgical, neuroradiological, pathological, radiotherapy and chemotherapy facilities and personnel. In addition the treating centre should have the capacity to effectively screen and manage any tumour and treatment-associated complications. These requirements have made it difficult for many low and middle-income countries (LMIC) centres to offer curative treatment. This article provides management recommendations for children with standard-risk medulloblastoma (localised tumours in children over the age of 3-5 years) according to the level of facilities available.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.199
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.273
Teacher spread0.258 · 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.

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

Citations81
Published2014
Admission routes1
Has abstractyes

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