← Back to cohort
MC1R variants in childhood and adolescent melanoma: a retrospective pooled analysis of a multicentre cohort
Cristina Pellegrini, Francesca Botta, Daniela Massi, Claudia Martorelli, Fabio Facchetti, Sara Gandini, Patrick Maisonneuve, Marie‐Françoise Avril, Florence Démenais, Brigitte Bressac–de Paillerets, Veronica Höiom, Anne Ε. Cust, Hoda Anton‐Culver, Stephen B. Gruber, Richard P. Gallagher, Loraine D. Marrett, Roberto Zanetti, Terence Dwyer, Nancy E. Thomas, Colin B. Begg, Marianne Berwick, Susana Puig, Míriam Potrony, Eduardo Nagore, Paola Ghiorzo, Chiara Menin, Ausilia Maria Manganoni, Monica Rodolfo, S. Brugnara, Emanuela Passoni, Lidija Kandolf Sekulović, Federica Baldini, Gabriella Guida, Alexandros Stratigos, Fezal Özdemir, Fabrizio Ayala, Ricardo Fernández‐de‐Misa, Pietro Quaglino, Gloría Ribas, Antonella Romanini, Emilia Migliano, Ignazio Stanganelli, Peter A. Kanetsky, Maria Antonietta Pizzichetta, José C. García‐Borrón, Hongmei Nan, Maria Teresa Landi, Julian Little, Julia Newton‐Bishop, Francesco Sera, Maria Concetta Fargnoli, Sara Raimondi, Mauro Alaibac, Andrea Ferrari, Barbara Valeri, Mariacristina Sicher, Daniela Mangiola, Gianluca Nazzaro, Giulio Tosti, Giovanni Mazzarol, Giuseppe Giudice, Simone Ribero, Chiara Astrua, Laura Mazzoni, Irene Orlow, Urvi Mujumdar, Amanda Hummer, Klaus J. Busam, Pampa Roy, Rebecca Canchola, Brian Clas, Yvette Monroe, Bruce K. Armstrong, Anne Kricker, Melisa Litchfield, Paul Tucker, Nicola Stephens, Teresa Switzer, Beth Theis, Lynn From, Noori Chowdhury, Louise Vanasse, Mark P. Purdue, David Northrup, Stefano Rosso, Carlotta Sacerdote, Nancy Leighton, Maureen Gildea, Joe Bonner, Joanne Jeter, Judith B. Klotz, Homer Wilcox, Helen A. Weiss, Robert C. Millikan, Dianne Mattingly, Jon Player, Chiu‐Kit Tse, Timothy R. Rebbeck, Amy Walker, Saarene Panossian, R. B. Setlow, Harvey W. Mohrenweiser, Philippe Autier, Jiali Han, Saverio Caini, Albert Hofman, Manfred Kayser, Fan Liu, Tamar Nijsten, Andre G. Uitterlinden, Rajiv Kumar, D. Timothy Bishop, Faye Elliott, DeAnn Lazovich, David Polsky, Johan Hansson, Lorenza Pastorino, Nelleke A. Gruis, Jan Nico Bouwes Bavinck, Paula Aguilera, Célia Bádenas, Cristina Carrera, Pol Giménez‐Xavier, Josep Malvehy, Gemma Tell‐Martí, Leigh Blizzard, Jennifer Cochrane, Wojciech Branicki, Tadeusz Dębniak, Niels Morling, Peter Johansen, Susan T. Mayne, A. Bale, Brenda Cartmel, Leah M. Ferrucci, Ruth M. Pfeiffer, Giuseppe Palmieri, Katerina Kypreou, A. Bowcock, Lynn A. Cornelius, Tomonori Motokawa, Sumiko Anno, Per Helsing, Per Arne Andresen, Stefania Guida, Terence H Wong
Bibliographic record
VenueThe Lancet Child & Adolescent Health · 2019
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsUniversity of OttawaCancer Care OntarioUniversity of British Columbia
FundersNational Cancer InstituteInstituto de Salud Carlos IIIInstitut Gustave-RoussyFundació la Marató de TV3Agència de Gestió d'Ajuts Universitaris i de RecercaAssociazione Italiana per la Ricerca sul CancroGeneralitat de CatalunyaFundación Científica Asociación Española Contra el CáncerEuropean CommissionCancer Research UKCentres de Recerca de CatalunyaSociety for Pediatric Dermatology
KeywordsMedicineRetrospective cohort studyCohortCohort studyMelanomaPediatricsOncologyMEDLINEInternal medicineBiologyCancer research
Abstract
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 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.
metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.732
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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.
Opus teacher head0.010
GPT teacher head0.259
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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
Citations19
Published2019
Admission routes1
Has abstractno