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Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study
Ingrid S. van Maurik, Stephanie J. B. Vos, Isabelle Bos, Femke H. Bouwman, Charlotte E. Teunissen, Philip Scheltens, Frederik Barkhof, Lutz Frölich, Johannes Kornhuber, Jens Wiltfang, Wolfgang Maier, Oliver Peters, Eckart Rüther, Flavio Nobili, Giovanni B. Frisoni, Luiza Spiru, Yvonne Freund‐Levi, Åsa K. Wallin, Harald Hampel, Hilkka Soininen, Magda Tsolaki, Frans R.J. Verhey, Iwona Kłoszewska, Patrizia Mecocci, Bruno Vellas, Simon Lovestone, Samantha Galluzzi, Sanna-Kaisa Herukka, Isabel Santana, Inês Baldeiras, Alexandre de Mendonça, Dina Silva, Gaël Chételat, Stéphanie Egret, Sebastian Palmqvist, Oskar Hansson, Pieter Jelle Visser, Johannes Berkhof, Wiesje M. van der Flier
Bibliographic record
VenueThe Lancet Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Institute on AgingJohnson and Johnson Pharmaceutical Research and DevelopmentFuel Cell Technologies ProgramFifth Framework ProgrammeCanadian Institutes of Health ResearchParkinsonfondenDanone Research Centre for Specialised NutritionEuropean Regional Development FundEuropean Research CouncilGE HealthcareFondation SegréH. Lundbeck A/SMarcus och Amalia Wallenbergs minnesfondNational Institute of Biomedical Imaging and BioengineeringAmsterdam NeuroscienceSkånes universitetssjukhusPfizer PharmaceuticalsInnovative Medicines InitiativeAXA Research FundFondation Plan AlzheimerServierAmerican Liver FoundationKnut och Alice Wallenbergs StiftelseAustralian GovernmentLunds UniversitetVetenskapsrådetNIHR Imperial Biomedical Research CentreFoundation for the National Institutes of HealthEisaiUCLH Biomedical Research CentreFondation pour la Recherche sur la BiodiversiteHôpitaux Universitaires de GenèveFondation Vaincre AlzheimerBundesministerium für Bildung und ForschungAlzheimer NederlandSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungInstitut National de la Santé et de la Recherche MédicaleBoehringer IngelheimSeventh Framework ProgrammeNovartis Pharmaceuticals CorporationMerckAssociation pour la Recherche sur le CancerDoD Alzheimer's Disease Neuroimaging InitiativeAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsBiogenAgence Nationale de la RechercheF. Hoffmann-La RocheAlzheimer's AssociationEuropean Federation of Pharmaceutical Industries and AssociationsTakeda Pharmaceutical CompanyHjärnfondenAstraZenecaEuropean CommissionAbbVieNederlandse Organisatie voor Wetenschappelijk OnderzoekNovartisBristol-Myers SquibbEli Lilly and CompanyRocheZonMwNational Institutes of HealthAlzheimer's Drug Discovery FoundationNederlandse Brandwonden StichtingNational Science FoundationFundação para a Ciência e a TecnologiaEU Joint Programme – Neurodegenerative Disease ResearchOryzon GenomicsSweden-America Foundation
KeywordsDementiaBiomarkerOncologyMedicineCohortAlzheimer's Disease Neuroimaging InitiativeInternal medicineDiseaseGerontology
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 score0.082
Threshold uncertainty score0.445
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 head0.052
GPT teacher head0.332
Teacher spread0.281 · 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
Citations145
Published2019
Admission routes1
Has abstractno