Bibliographic record
Abstract
BACKGROUND: Frontotemporal dementia is the most common form of dementia impacting those under the age of 60. It is estimated that 30% of affected persons have a genetic predisposition to this disease, with mutations in the genes encoding progranulin (GRN), chromosome 9 open reading frame 72(C9orf72), and microtubule associated protein tau (MAPT). Mutations in MAPT were discovered in 1998, yet to date, there have been no therapies or multisite clinical trials available to families. METHOD: To coordinate the sharing of information and advocacy efforts, a group of family kindreds impacted by MAPT created a non-profit organization and database for families in November 2023. RESULT: Spanning over 5 generations across the United States, Canada, and Europe, we have identified 17 family kindreds with 70 members living or deceased with symptomatic disease, 22 presymptomatic positive carriers, 34 tested negative/non-carriers, and 116 at risk or untested family members. CONCLUSION: We are aware of the burden of this disease on patients and families and the lack of resources to efficiently diagnose and treat FTD. We are working collaboratively with other genetic FTD organizations and institutions to further reach MAPT families in an international effort to provide support for MAPT families and gene carriers, identify areas for advocacy, promote research, and to contribute to future therapeutics. Fueled by the past trauma of watching my loved ones succumb to FTD, terrified of how FTD will dictate my future, and fighting for those whose minds are currently failing them.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.006 |
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.
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 source (direct Gemma or distilled Codex), not a consensus.
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".