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Record W3045281070 · doi:10.1016/j.ajhg.2020.06.015

Bi-allelic HPDL Variants Cause a Neurodegenerative Disease Ranging from Neonatal Encephalopathy to Adolescent-Onset Spastic Paraplegia

2020· article· en· W3045281070 on OpenAlexaff
Ralf A. Husain, Mona Grimmel, Matias Wagner, J. Christopher Hennings, Christian Marx, René G. Feichtinger, Abdelkrim Saadi, Kevin Rostásy, Florentine Radelfahr, Andrea Bevot, Marion Döbler‐Neumann, Hans Hartmann, Laurence Colleaux, Isabell Cordts, Xenia Kobeleva, Hossein Darvish, Somayeh Bakhtiari, Michael C. Kruer, Arnaud Besse, Andy Cheuk‐Him Ng, Diana Chiang, François V. Bolduc, Abbas Tafakhori, Shrikant Mane, Saghar Ghasemi Firouzabadi, Antje K. Huebner, Rebecca Buchert, Stefanie Beck‐Woedl, Amelie J. Müller, Lucia Laugwitz, Thomas Nägele, Zhao‐Qi Wang, Tim M. Strom, Marc Sturm, Thomas Meitinger, Thomas Klockgether, Olaf Rieß, Thomas Klopstock, Ulrich Brandl, Christian A. Hübner, Marcus Deschauer, Johannes A. Mayr, Penelope E. Bonnen, Ingeborg Krägeloh‐Mann, Saskia B. Wortmann, Tobias B. Haack

Bibliographic record

VenueThe American Journal of Human Genetics · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeurological diseases and metabolism
Canadian institutionsUniversity of Alberta
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeNational Institutes of HealthBundesministerium für Bildung und ForschungRadboud Universitair Medisch CentrumCosmetic Surgery FoundationDeutsche ForschungsgemeinschaftE-Rare
KeywordsMedicineSpasticParaplegiaAlleleHereditary spastic paraplegiaEncephalopathyDiseaseCerebral palsyPediatricsBiologyGeneticsInternal medicinePhysical therapyPsychiatryPhenotypeGeneSpinal cord

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.046
GPT teacher head0.286
Teacher spread0.240 · 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

Citations54
Published2020
Admission routes1
Has abstractno

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