MétaCan
Menu
Back to cohort
Record W4396578551 · doi:10.1111/tid.14273

Clinicopathologic conference: Bloodstream infection in an allogeneic hamatopoietic cell transplant: Thinking beyond the usual

2024· article· en· W4396578551 on OpenAlexfundno aff
Kim Yeoh, Cornelia Lass‐Flörl, Frédéric Lamoth, Monica A. Slavin, Eloise Williams, Dionysios Neofytos

Bibliographic record

VenueTransplant Infectious Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsnot available
FundersInstitute of Infection and ImmunityPeter MacCallum Cancer Centre
KeywordsMedicineCytarabineMelphalanChemotherapyFludarabineMultiple myelomaInduction chemotherapyMyeloid leukemiaAutologous stem-cell transplantationAzacitidineChemotherapy regimenOncologyInternal medicineSurgeryCyclophosphamide

Abstract

fetched live from OpenAlex

This case involves a 53-year-old female with concurrent acute myeloid leukemia (AML) and multiple myeloma. She underwent cytarabine and daunorubicin (7+3) induction chemotherapy followed by cytarabine (HiDAC) consolidation, with an early AML relapse requiring azacitidine and venetoclax therapy. She achieved complete remission and incomplete count recovery. Following fludarabine, melphalan, and thymoglobulin induction chemotherapy, she underwent an allogeneic stem cell transplant with failure to engraft, requiring autologous stem cell rescue, buffy coat, and granulocyte transfusions, eventually presenting with a diffuse skin rash consistent with Steven-Johnson syndrome and toxic epidermal necrolysis, persistent neutropenic fevers and positive blood cultures.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.295
Teacher spread0.273 · 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 designCase report
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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTransplant Infectious DiseaseSame topicNeutropenia and Cancer InfectionsFrench-language works237,207