Citizens United in Research for Epilepsy (CURE)
Bibliographic record
Abstract
Subjects : Basic mechanisms of epilepsy; Acquired epilepsies; Pediatric epilepsies; SUDEP; Treatment-resistant epilepsies; and Sleep & epilepsy. Purpose : The award seeks to promote the careers of young epilepsy investigators to allow them to develop a research focus independent of their mentor(s). Eligibility : You must fall into one of the following categories to be eligible for the Taking Flight Award: A senior postdoctoral fellow who has a minimum of 3 years postdoctoral experience; A clinical fellow who is a Neurology Resident in his/her Neurology training and considering Epilepsy Fellowships; Newly appointed faculty within one year of having completed postdoctoral training. International applicants are welcome; you do not have to be a US citizen or working in the US to apply for this award. All materials must be submitted in English. Type : Award Value : US$100,000 Length of Study : One year Country of Study : Any country Application Procedure : See website for further details. Closing Date : 1 April Additional Information : www.cureepilepsy.org/grants-program/#:~:text=The%20Taking%20Flight%20Award%20(1,of%20their%20mentor(s) .
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.094 | 0.041 |
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".