MétaCan
Menu
Back to cohort
Record W4313575102 · doi:10.1016/j.leukres.2023.107016

Canadian evidence-based guideline for frontline treatment of chronic lymphocytic leukemia: 2022 update

2023· review· en· W4313575102 on OpenAlexaffabout
Carolyn Owen, Versha Banerji, Nathalie A. Johnson, Alina S. Gerrie, Andrew Aw, Christine Chen, Sue Robinson

Bibliographic record

VenueLeukemia Research · 2023
Typereview
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie UniversityUniversity of TorontoPrincess Margaret Cancer CentreFoothills Medical CentreOttawa HospitalSpinal Cord Injury BCJewish General HospitalCancerCare Manitoba
Fundersnot available
KeywordsGuidelineChronic lymphocytic leukemiaFront lineMedicineFirst line treatmentLeukemiaFamily medicineIntensive care medicineInternal medicinePolitical sciencePathologyChemotherapy

Abstract

fetched live from OpenAlex

Chronic lymphocytic leukemia (cll) is the most common adult leukemia in North America. In 2018, the first unified national guideline in Canada was developed for the front-line treatment of cll that helped guide treatment across the country. As an update in 2022, a group of clinical experts from across Canada came together to provide input and guidance that included new and innovative treatments and approaches that will continue to provide health care professionals with clear guidance on the first-line management of cll. Recommendations were provided in consensus based on available evidence for the first-line treatment of cll.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.836
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0140.004

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 head0.286
GPT teacher head0.487
Teacher spread0.201 · 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

Citations19
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueLeukemia ResearchSame topicChronic Lymphocytic Leukemia ResearchFrench-language works237,207