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Record W2928090978 · doi:10.1016/j.devcel.2019.03.001

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution

2019· review· en· W2928090978 on OpenAlexaff
Deanne Taylor, Bruce J. Aronow, Kai Tan, Kathrin M. Bernt, Nathan Salomonis, Casey S. Greene, Alina Frolova, Sarah E. Henrickson, Andrew D. Wells, Liming Pei, Jyoti K. Jaiswal, Jeffrey A. Whitsett, Kathryn E. Hamilton, Sonya A. MacParland, Judith R. Kelsen, Robert O. Heuckeroth, S. Steven Potter, Laura A. Vella, Natalie A. Terry, Louis R. Ghanem, Benjamin C. Kennedy, Ingo Helbig, Kathleen E. Sullivan, Leslie Castelo‐Soccio, Arnold Kreigstein, Florian Herse, Martijn C. Nawijn, Gerard H. Koppelman, Melissa Haendel, Nomi L. Harris, Jo Lynne Rokita, Yuanchao Zhang, Aviv Regev, Orit Rozenblatt–Rosen, Jennifer Rood, Timothy L. Tickle, Roser Vento‐Tormo, Saif Alimohamed, Monkol Lek, Jessica C. Mar, Kathleen M. Loomes, David M. Barrett, Prech Uapinyoying, Alan H. Beggs, Pankaj B. Agrawal, Yi-Wen Chen, Amanda B. Muir, Lana X. Garmire, Scott B. Snapper, Javad Nazarian, Steven H. Seeholzer, Hossein Fazelinia, Larry N. Singh, Robert B. Faryabi, Pichai Raman, Noor Dawany, Hongbo Xie, Batsal Devkota, Sharon J. Diskin, Stewart A. Anderson, Eric Rappaport, William H. Peranteau, Kathryn A. Wikenheiser‐Brokamp, Sarah A. Teichmann, Douglas C. Wallace, Tao Peng, Yangyang Ding, Man S. Kim, Yi Xing, Sek Won Kong, Carsten G. Bönnemann, Kenneth D. Mandl, Peter S. White

Bibliographic record

VenueDevelopmental Cell · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentU.S. National Library of MedicineNational Institute of Environmental Health SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Center for Advancing Translational SciencesNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteNational Institute of Mental HealthEuropean Hematology AssociationAlex's Lemonade Stand Foundation for Childhood CancerNational Cancer InstituteNational Institutes of HealthCincinnati Children's Hospital Medical CenterMuscular Dystrophy AssociationGordon and Betty Moore FoundationNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Allergy and Infectious DiseasesHoward Hughes Medical Institute
KeywordsBiologyCellMorphogenesisComputational biologyAtlas (anatomy)Cell growthCell biologyGeneHuman Protein AtlasHuman cellHuman diseaseGeneticsEvolutionary biologyAnatomyProtein expression

Abstract

fetched live from OpenAlex

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.005

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 head0.043
GPT teacher head0.274
Teacher spread0.231 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations68
Published2019
Admission routes1
Has abstractyes

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