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Record W4393275916 · doi:10.21203/rs.3.rs-4103685/v1

Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration

2024· preprint· en· W4393275916 on OpenAlexaff
Rowan Saloner, Adam M. Staffaroni, Eric B. Dammer, Erik C. B. Johnson, Emily W. Paolillo, Amy B. Wise, Hilary W. Heuer, Leah K. Forsberg, Argentina Lario Lago, Julia D Webb, Jacob W. Vogel, Alexander Santillo, Oskar Hansson, Joel H. Kramer, Bruce L. Miller, Jingyao Li, Joseph Loureiro, Rajeev Sivasankaran, Kathleen A. Worringer, Nicholas T. Seyfried, Jennifer S. Yokoyama, William W. Seeley, Salvatore Spina, Lea T. Grinberg, Lawren VandeVrede, Peter A. Ljubenkov, Ece Bayram, Andrea Bozoki, Danielle Brushaber, Ciaran Considine, Gregory S. Day, Bradford C. Dickerson, Kimiko Domoto‐Reilly, Kelley Faber, Douglas Galasko, Daniel H. Geschwind, Nupur Ghoshal, Neill R. Graff‐Radford, Chadwick M. Hales, Lawrence S. Honig, Ging‐Yuek Robin Hsiung, Edward D. Huey, John Kornak, Walter K. Kremers, Maria I. Lapid, Suzee Lee, Irene Litvan, Corey T. McMillan, Mario F. Mendez, Toji Miyagawa, Alexander Pantelyat, Belén Pascual, Henry L. Paulson, Leonard Petrucelli, Peter Pressman, Eliana Marisa Ramos, Katya Rascovsky, Erik D. Roberson, Rodolfo Savica, Allison Snyder, A. Campbell Sullivan, Maria Carmela Tartaglia, Marijne Vandebergh, Bradley F. Boeve, Howie Rosen, Julio C. Rojas, Adam L. Boxer, Kaitlin B. Casaletto

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersNational Center for Advancing Translational SciencesParkinsonfondenNational Institutes of HealthVetenskapsrådetCurePSPGHR FoundationLarry L. Hillblom FoundationNational Institute on AgingKnut och Alice Wallenbergs StiftelseLunds UniversitetAlzheimer's Association
KeywordsFrontotemporal lobar degenerationCerebrospinal fluidProteomePathologyScale (ratio)NeuroscienceMedicineComputational biologyFrontotemporal dementiaBiologyBioinformaticsGeographyDiseaseCartography

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.314
Teacher spread0.299 · 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

Citations8
Published2024
Admission routes1
Has abstractno

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