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Record W3116623649 · doi:10.1016/j.xpro.2020.100248

Enriching for human acute myeloid leukemia stem cells using reactive oxygen species-based cell sorting

2020· article· en· W3116623649 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSTAR Protocols · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Institutes of HealthNational Cancer InstitutePrincess Margaret Cancer FoundationEdward P. Evans FoundationLeukemia and Lymphoma Society
KeywordsStem cellMyeloid leukemiaLeukemiaReactive oxygen speciesBiologyStem cell markerImmunologyCancer researchCell biology

Abstract

fetched live from OpenAlex

Isolation of leukemia stem cells presents a challenge due to the heterogeneity of the immunophenotypic markers commonly used to identify blood stem cells. Several studies have reported that relative levels of reactive oxygen species (ROS) can be used to enrich for stem cell populations, suggesting a potential alternative to surface antigen-based methods. Here, we describe a protocol to enrich for stem cells from human acute myeloid leukemia specimens using relative levels of ROS. This protocol provides consistent enrichment of leukemia stem cells. For complete details on the use and execution of this protocol, please refer to Lagadinou et al. (2013) and Pei et al. (2018).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.089
GPT teacher head0.362
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