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Record W3009342698 · doi:10.3390/ijerph17051783

Resources-Stratified Guidelines for Classical Hodgkin Lymphoma

2020· review· en· W3009342698 on OpenAlexaff
Allan Relecom, Massimo Federico, Joseph M. Connors, Bertrand Coiffier, Irène Biasoli, Alden A. Moccia, Gilles Salles, Thomas McKee, Raymond Miralbell, Peter Borchmann, John Kuruvilla, Peter Johnson, Franco Cavalli, Martine Delavy, Pierre‐Yves Dietrich, Antoine Flahault

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typereview
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoBC Cancer Agency
FundersMorphoSysCancer Research UKIncyteCelgeneGilead SciencesServierAmgenPfizerBristol-Myers Squibb
KeywordsLymphomaMedicineHodgkin lymphomaModalitiesMalignancyDiseaseHealth careOncologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Hodgkin lymphoma is a haematological malignancy predominantly affecting young adults. Hodgkin lymphoma is a highly curable disease by current treatment standards. Latest treatment guidelines for Hodgkin lymphoma however imply access to diagnostic and treatment modalities that may not be available in settings with restricted healthcare resources. Considerable discrepancies in Hodgkin lymphoma patient survival exist, with poorer outcomes reported in resources-constrained settings. Resources-stratified guidelines for diagnosis, staging and treatment of Hodgkin lymphoma were derived in an effort to optimize patient outcome provided a given setting of available resources. These guidelines were derived based on the framework of the Breast Health Global Initiative stratifying resource levels in basic, core, advanced and maximal categories.

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 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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.344
GPT teacher head0.510
Teacher spread0.166 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations14
Published2020
Admission routes1
Has abstractyes

Explore more

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