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Contribution to Alzheimer's disease risk of rare variants in TREM2, SORL1, and ABCA7 in 1779 cases and 1273 controls

2017· article· en· W2735794637 on OpenAlexaff
Céline Bellenguez, Camille Charbonnier, Benjamin Grenier‐Boley, Olivier Quenez, Kilan Le Guennec, Gaël Nicolas, Ganesh Chauhan, David Wallon, Stéphane Rousseau, Anne Richard, Anne Boland, Guillaume Bourque, Hans Markus Münter, Robert Olaso, Vincent Meyer, Adeline Rollin‐Sillaire, Florence Pasquier, Luc Letenneur, Richard Redon, Jean‐François Dartigues, Christophe Tzourio, Thierry Frébourg, Mark Lathrop, Jean‐François Deleuze, Didier Hannequin, Emmanuelle Génin, Philippe Amouyel, Stéphanie Debette, Jean‐Charles Lambert, Dominique Campion, Olivier Martinaud, Aline Zaréa, Stéphanie Bombois, Marie‐Anne Mackowiak, Vincent Deramecourt, Agnès Michon, Isabelle Le Ber, Bruno Dubois, Olivier Godefroy, Frédérique Etcharry‐Bouyx, Valérie Chauviré, Ludivine Chamard, Eric Berger, Éloi Magnin, Sophie Auriacombe, François Tison, Vincent de la Sayette, Dominique Castan, Elsa Dionet, François Sellal, Olivier Rouaud, Christel Thauvin, Olivier Moreaud, Mathilde Sauvée, Maïté Formaglio, Hélène Mollion, Isabelle Roullet‐Solignac, Alain Vighetto, Bernard Croisile, Mira Didic, Olivier Félician, Lejla Koric, Mathieu Ceccaldi, Audrey Gabelle, Cécilia Marelli, Pierre Labauge, Thérèse Jonveaux, Martine Vercelletto, Claire Boutoleau‐Bretonnière, Giovanni Castelnovo, Claire Paquet, Julien Dumurgier, Jacques Hugon, Foucauld De Boisgueheneuc, Serge Belliard, Serge Bakchine, Marie Sarazin, Marie‐Odile Barrellon, Bernard Laurent, Frédéric Blanc, Jérémie Pariente, Snejana Jurici

Bibliographic record

VenueNeurobiology of Aging · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsMcGill University and Génome Québec Innovation Centre
FundersFédération pour la Recherche sur le CerveauInstitut National de la Santé et de la Recherche MédicaleAgence Nationale de la RechercheDevelopment of Innovative Strategies for a Transdisciplinary approach to ALZheimer's diseaseCentre National de la Recherche ScientifiqueEU Joint Programme – Neurodegenerative Disease Research
KeywordsTREM2Missense mutationGeneticsExome sequencingBiologyExomeAlleleMinor allele frequencyGenetic associationEarly-onset Alzheimer's diseaseGenome-wide association studyGeneAlzheimer's diseaseSingle-nucleotide polymorphismDiseaseAllele frequencyMutationMedicineGenotypeInternal medicine

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)0.002
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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.285
Teacher spread0.254 · 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

Citations170
Published2017
Admission routes1
Has abstractno

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