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Record W2766745670 · doi:10.1182/blood-2017-07-793760

Infectious complications of CD19-targeted chimeric antigen receptor–modified T-cell immunotherapy

2017· article· en· W2766745670 on OpenAlexaff
Joshua A. Hill, Daniel Li, Kevin A. Hay, Margaret L. Green, Sindhu Cherian, Xueyan Chen, Stanley R. Riddell, David G. Maloney, Michael Boeckh, Cameron J. Turtle

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of British Columbia
FundersNational Cancer InstituteJuno TherapeuticsNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesWashington State University
KeywordsChimeric antigen receptorImmunotherapyMedicineCD19AntigenImmunologyVirologyCancer researchImmune system

Abstract

fetched live from OpenAlex

cells per kg) had a higher infection density within 28 days in an adjusted model of baseline characteristics. Cytokine release syndrome (CRS) severity was the only factor after CAR-T-cell infusion associated with infection in a multivariable analysis. The incidence of infections was comparable to observations from clinical trials of salvage chemoimmunotherapies in similar patients. This trial was registered at www.clinicaltrials.gov as #NCT01865617.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.317
Teacher spread0.287 · 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 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

Citations566
Published2017
Admission routes1
Has abstractyes

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