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Record W2120309731 · doi:10.3109/10428194.2014.970548

Development and characterization of a Mantle Cell Lymphoma Cell Bank in the American Type Culture Collection

2014· article· en· W2120309731 on OpenAlexaff
Laura K. Fogli, Michael E. Williams, Joseph M. Connors, Yvonne Reid, Kathleen C. Brown, Owen A. O’Connor

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2014
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMantle cell lymphomaLymphomaCell cultureMedicineMalignancyDiseaseCancer researchBiologyPathologyGenetics

Abstract

fetched live from OpenAlex

Mantle cell lymphoma (MCL) is a rare B-cell malignancy that carries a relatively poor prognosis compared to other forms of non-Hodgkin lymphoma. Standardized preclinical tools are desperately required to hasten the discovery and translation of promising new treatments for MCL. Via an initiative organized through the Mantle Cell Lymphoma Consortium and the Lymphoma Research Foundation, we gathered MCL cell lines from laboratories around the world to create a characterized MCL Cell Bank at the American Type Culture Collection (ATCC). Initiated in 2006, this collection now contains eight cell lines, all of which have been rigorously characterized and are now stored and available for distribution to the general scientific community. We believe the awareness and use of these standardized cell lines will decrease variability between investigators, harmonize international research efforts, improve our understanding of the pathogenesis of the disease and hasten the development of novel treatment strategies.

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)0.005
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0040.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0140.012

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 head0.007
GPT teacher head0.218
Teacher spread0.211 · 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 designBench or experimental
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

Citations3
Published2014
Admission routes1
Has abstractyes

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