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Record W2986279507 · doi:10.1016/s1474-4422(19)30354-0

Serum neurofilament light chain in genetic frontotemporal dementia: a longitudinal, multicentre cohort study

2019· article· en· W2986279507 on OpenAlexafffund
Emma L. van der Ende, Lieke Meeter, Jackie M. Poos, Jessica Panman, Lize C. Jiskoot, Elise G.P. Dopper, Janne M. Papma, Frank Jan de Jong, Inge M.W. Verberk, Charlotte E. Teunissen, Dimitris Rizopoulos, Carolin Heller, Rhian S. Convery, Katrina Moore, Martina Bocchetta, Mollie Neason, David M. Cash, Barbara Borroni, Daniela Galimberti, Raquel Sánchez‐Valle, Robert Laforce, Fermín Moreno, Matthis Synofzik, Caroline Graff, Mario Masellis, Maria Carmela Tartaglia, James B. Rowe, Rik Vandenberghe, Elizabeth Finger, Fabrizio Tagliavini, Alexandre de Mendonça, Isabel Santana, Christopher Butler, Simon Ducharme, Alexander Gerhard, Adrian Danek, Johannes Levin, Markus Otto, Giovanni B. Frisoni, Stefano F. Cappa, Yolande A.L. Pijnenburg, Jonathan D. Rohrer, John C. van Swieten, Martin N. Rossor, Jason D. Warren, Nick C. Fox, Ione Woollacott, Rachelle Shafei, Caroline Greaves, Rita Guerreiro, José Brás, David L. Thomas, Jennifer Nicholas, Simon Mead, Rick van Minkelen, Myriam Barandiarán, Begoña Indakoetxea, Alazne Gabilondo, Mikel Tainta, María de Arriba, Ana Gorostidi, Miren Zulaica, Jorge Villanúa, Zigor Díaz, Sergi Borrego‐Écija, Jaume Olives, Albert Lladó, Mircea Balasa, Anna Antonell, Núria Bargalló, Enrico Premi, Maura Cosseddu, Stefano Gazzina, Alessandro Padovani, Roberto Gasparotti, Silvana Archetti, Sandra E. Black, Sara Mitchell, Ekaterina Rogaeva, Morris Freedman, Ron Keren, David F. Tang‐Wai, Linn Öijerstedt, Christin Andersson, Vesna Jelić, Håkan Thonberg, Andrea Arighi, Chiara Fenoglio, Elio Scarpini, Giorgio Fumagalli, Thomas Cope, Carolyn Timberlake, Timothy Rittman, Christen Shoesmith, Rosa Rademakers, Carlo Wilke, Hans‐Otto Karnath, Benjamin Bender, Rose Bruffaerts, Mathieu Vandenbulcke, Catarina B. Ferreira, Gabriel Miltenberger, Carolina Maruta, Ana Verdelho, Sònia Afonso, Ricardo Taipa, Paola Caroppo, Giuseppe Di Fede, Giorgio Giaccone, Sara Prioni, Veronica Redaelli, Giacomina Rossi, Pietro Tiraboschi, Diana Duro, Maria Rosário Almeida, Miguel Castelo‐Branco, Maria João Leitão, Miguel Tábuas‐Pereira, Beatriz Santiago, Serge Gauthier, Sonja Schönecker, Elisa Semler, Sarah Anderl‐Straub, Luisa Benussi, Giuliano Binetti, Roberta Ghidoni, Michela Pievani, Gemma Lombardi, Benedetta Nacmias, Camilla Ferrari, Valentina Bessi

Bibliographic record

VenueThe Lancet Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill University Health CentreWestern UniversityUniversity of TorontoSunnybrook HospitalOccupational Cancer Research CentreUniversité Laval
FundersMedical Research CouncilStockholm läns landstingStichting DioraphteHjärnfondenVetenskapsrådetMinistero della SaluteAlzheimer’s Research UKEuropean CommissionZonMwFondation Thierry LatranIonis PharmaceuticalsWellcome TrustDeutsche ForschungsgemeinschaftAlzheimerfondenFundació la Marató de TV3Bundesministerium für Bildung und ForschungNational Institute for Health and Care ResearchAlzheimer SocietyKarolinska InstitutetEU Joint Programme – Neurodegenerative Disease ResearchAbbVie
KeywordsFrontotemporal dementiaC9orf72MedicineDementiaCohortOncologyGenetic testingFrontotemporal lobar degenerationInternal medicineCohort studyPediatricsPsychiatryDisease

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)0.003
metaresearch head score (Gemma)0.004
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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.294
Teacher spread0.265 · 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

Citations186
Published2019
Admission routes2
Has abstractno

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