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Record W4308789228 · doi:10.1159/000526021

Innovating Therapies for Down Syndrome: An International Virtual Conference of the T21 Research Society

2022· article· en· W4308789228 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular Syndromology · 2022
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsMcGill University
FundersNational Institutes of Health
KeywordsCoronavirus disease 2019 (COVID-19)Down syndromePandemicMedicineNeurologyTrisomyPsychiatryNeurosciencePsychologyDiseaseBiologyPathology

Abstract

fetched live from OpenAlex

Research focused on Down syndrome continued to gain momentum in the last several years and is advancing our understanding of how trisomy 21 (T21) modifies molecular and cellular processes. The Trisomy 21 Research Society (T21RS) is the premier scientific organization for researchers and clinicians studying Down syndrome. During the COVID pandemic, T21RS held its first virtual conference program, sponsored by the University of California at Irvine, on June 8-10, 2021 and brought together 342 scientists, families, and industry representatives from over 25 countries to share the latest discoveries on underlying cellular and molecular mechanisms of T21, cognitive and behavioral changes, and comorbidities associated with Down syndrome, including Alzheimer's disease and Regression Disorder. Presentations of 91 cutting-edge abstracts reflecting neuroscience, neurology, model systems, psychology, biomarkers, and molecular and pharmacological therapeutic approaches demonstrate the compelling interest and continuing advancement toward innovating biomarkers and therapies aimed at ameliorating health conditions associated with T21.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.124
GPT teacher head0.401
Teacher spread0.277 · 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