MétaCan
Menu
Back to cohort
Record W4244065648 · doi:10.1038/s41375-019-0672-9

Correction: Minimal residual disease quantification by flow cytometry provides reliable risk stratification in T-cell acute lymphoblastic leukemia

2019· erratum· en· W4244065648 on OpenAlexaff
Signe Modvig, H O Madsen, Sanna Siitonen, Susanne Rosthøj, Anne Tierens, Vesa Juvonen, Liv Osnes, Helen Vålerhaugen, Magnus Hultdin, Ingrid Thörn, Rėda Matuzevičienė, Mindaugas Stoškus, Millaray Marincevic, Linda Fogelstrand, Aili Lilleorg, N. Toft, Ólafur G. Jónsson, Kaie Pruunsild, Goda Vaitkevičienė, Kim Vettenranta, Bendik Lund, Jonas Abrahamsson, Kjeld Schmiegelow, Hanne Vibeke Marquart

Bibliographic record

VenueLeukemia · 2019
Typeerratum
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMinimal residual diseaseRisk stratificationFlow cytometryLymphoblastic LeukemiaMedicineResidualOncologyDiseaseLeukemiaStratification (seeds)ImmunologyInternal medicinePathologyBiologyComputer science

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)0.006
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.095
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0590.033

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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractno

Explore more

Same venueLeukemiaSame topicAcute Lymphoblastic Leukemia researchFrench-language works237,207