Guidelines for the use of flow cytometry and cell sorting in immunological studies <sup>*</sup>
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.
Bibliographic record
Abstract
Funding Information: Mairi Mc Grath and Regina Stark thank Francesco Siracusa and Patrick Maschmeyer for providing data and Klaas van Gisbergen for helpful discussions. Philip E. Boulais and Paul S. Frenette are grateful to Dr. Sandra Pinho for helpful comments and suggestions. They thank the National Institutes of Health for their support (R01 grants DK056638, HL116340, HL097819 to P.S.F). They also thank the New York State Department of Health (NYSTEM Program) for shared facility (C029154) and research support (N13G-262) and the Leukemia and Lymphoma Society’s Translational Research Program. Funding Information: Acknowledgements: Enrico Lugli and Pratip K. Chattopadhyay were supported by grants from the Fondazione Cariplo (Grant Ricerca Biomedica 2012/0683), the Italian Ministry of Health (Bando Giovani Ricercatori GR-2011-02347324) and the European Union Marie Curie Career Integration Grant 322093 (all to E.L.). E.L. and P.K.C. are International Society for the Advancement of Cytometry (ISAC) Marylou Ingram scholars. Alice Yue and Ryan R. Brinkman were funded by Genome BC and NSERC. Klaus Warnatz received funding from the German Federal Ministry of Education and Research (BMBF 01EO1303) and the Deutsche Forschungsgemeinschaft (DECIDE, DFG WA 1597/4-1 and the TRR130). The Jung laboratory is supported by funds of the ERC and ISF. Henrik Mei is a 2017-2021 ISAC scholar. Antonio Cosma is supported by the French government program: “Investissement d’avenir: Equipements d’Excellence” (EQUIPEX)-2010 FlowCyTech, Grant number: ANR-10-EQPX-02-01. Henrik Mei is supported by the Deutsche Forschungsgemeinschaft (DFG; grants Me3644/5-1 and TRR130/TP24). Funding Information: The Immunology Database and Analysis Portal (ImmPort) system provides an archive of immunology research data generated by investigators mainly funded through the National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID), Division of Allergy, Immunology, and Transplantation (DAIT). It is an extensive data warehouse containing an integration of experimental and clinical trial data generated by dozens of assay types, including 63 flow cytometry and 5 CyTOF data sets. In addition, the ImmPort system also provides data analysis tools and it contains implicit knowledge and ‘‘best practices’’ for clinical and genomic studies in the form of nearly 50 templates for data deposition, management, and dissemination. ImmPort has been developed under the Bioinformatics Integration Support Contract (BISC) by the Northrop Grumman Information Technology Health
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it