MétaCan
Menu
Back to cohort
Record W3196277563 · doi:10.1016/s1470-2045(21)00454-x

Global characteristics and outcomes of SARS-CoV-2 infection in children and adolescents with cancer (GRCCC): a cohort study

2021· article· en· W3196277563 on OpenAlexaff
Sheena Mukkada, Nickhill Bhakta, Guillermo Chantada, Yi‐Chen Chen, Yuvanesh Vedaraju, Lane Faughnan, Maysam R. Homsi, Hilmarie Muñiz‐Talavera, Radhikesh Ranadive, Monika L. Metzger, Paola Friedrich, Asya Agulnik, Sima Jeha, Catherine G. Lam, Rashmi Dalvi, Laila Hessissen, Daniel C. Moreira, Victor M. Santana, Michael Sullivan, Éric Bouffet, Miguela A. Caniza, Meenakshi Devidas, Kathy Pritchard‐Jones, Carlos Rodríguez‐Galindo, Antonio Juan Ribelles, Adriana Balduzzi, Alaa Elhaddad, Alejandra Casanovas, Alejandra Garcia Velazquez, Aliaksandra Laptsevich, Alicia Chang, Alessandra Lamenha F. Sampaio, Almudena González Prieto, Álvaro Lassaletta, Amaranto Suarez M, Ana Patricia Alcasabas, Anca Coliţă, Andrés Morales La Madrid, Angélica Samudio, Annalisa Tondo, Antonella Colombini, Antonis Kattamis, Norma Araceli López Facundo, Arpita Bhattacharyya, Aurélia Alimi, Aurélie Phulpin, Barbora Vakrmanová, Başak Adaklı Aksoy, Benoît Brethon, Jator Brian Kobuin, Catherine Paillard, Catherine Vézina, Bozkurt Ceyhun, Cristiana Hentea, Cristina Meazza, Daniel Ortiz‐Morales, Daniela Arce Cabrera, Daniele Zama, Debjani Ghosh, Diana Ramírez-Rivera, Doris A. Calle Jara, Dragana Janić, Elianneth Rey Helo, Elodie Gouache, Enmanuel Isidoro Guerrero Quiroz, Enrique Lopez, Éric Thébault, Essy Maradiegue, Eva de Berranger, Fatma Soliman Elsayed Ebeid, Federica Galaverna, Federico Antillón‐Klussmann, Felipe Espinoza Chacur, Fernando Daniel Negro, Francesca Carraro, Francesca Compagno, Francisco M. Barriga, Gabriela Tamayo Pedraza, Gissela Sanchez Fernandez, Gita Naidu, Gülnür Tokuç, Hamidah Alias, Hannah Grace B. Segocio, Houda Boudiaf, Imelda Luna, Iris Maia, Itziar Astigarraga, Iván Maza, J. Vasquez, Janez Jazbec, Jelena Lazić, Jeniffer Beck Dean, Jérémie Rouger, Johanny Carolina Contreras González, Jorge Huerta‐Aragonés, José Luís Fuster, Juan Manuel Lemus Quintana, Julia Palma, Karel Švojgr, Karina Quintero, Karolina Malić Tudor, Kleopatra Georgantzi, Kris Ann P. Schultz, Laura Ureña Horno, Lidia Fraquelli, Linda Meneghello, Lobna Shalaby, Lola L Macias Mora, Lorna Renner, Luciana Nunes Silva, Luisa Sisinni, Mahmoud Hammad, M. Fernández Sanmartín, C Marcela Zubieta A, María Constanza Drozdowski, Maria Kourti, Marcela Palladino, M. Madrazo, Marilyne Poirée, Marina Popova, Mario Melgar, Marta Baragaño, Martha Avilés-Robles, Massimo Provenzi, Mecneide Mendes Lins, Mehmet Fatih Orhan, Milena Villarroel, Mónica Jerónimo, Mónica Varas Palma, Muhammad Rafie Raza, Mulindwa M Justin, Najma Shaheen, Nerea Domínguez‐Pinilla, Nicholas Whipple, Nicolás André, Ondřej Hrušák, Pablo Velasco, Pamela Zacasa Vargas, P. Mellado, Pascale Yola Gassant, Paulina Diaz Romero, Raffaella De Santis, Rejin Kebudi, Riza Boranbayeva, Roberto Vásquez, Romel A. Segura, Roy Rosado, Sandra Gómez, Sandra Raimbault, Sanjeeva Gunasekera, Sara Makkeyah, Sema Büyükkapu Bay, Sergio Gomez, Séverine Bouttefroy, Shahnoor Islam, Sherif Abouelnaga, Silvio Torres, Simone Cesaro, Sofia Nunes, Soraia Rouxinol, Sucharita Bhaumik, Symbat Saliyeva, Tamara Inostroza, Thelma Velásquez, Tint Myo Hnin, Ulrika Norén‐Nyström, Valentina Baretta, Yajaira Valentine Jiménez-Antolínez, Vanesa Pérez Alonso, Vanessa Ayer Miller, Virginie Gandemer, Viviana Lotero, Volha Mishkova, Wendy Gómez García, Yeva Margaryan, Yumna Syed

Bibliographic record

VenueThe Lancet Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsHospital for Sick Children
FundersNational Cancer InstituteNational Institutes of HealthAmerican Lebanese Syrian Associated Charities
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CohortMedicineCoronavirus disease 2019 (COVID-19)Cancer2019-20 coronavirus outbreakCohort studySars virusPediatricsVirologyInternal medicineDiseaseOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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 score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.429
Teacher spread0.373 · 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

Citations134
Published2021
Admission routes1
Has abstractno

Explore more

Same venueThe Lancet OncologySame topicCOVID-19 and healthcare impactsFrench-language works237,207