Proceedings of the inaugural Dark Genome Symposium: November 2022
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.
Bibliographic record
Abstract
In November 2022 the first Dark Genome Symposium was held in Boston, USA. The meeting was hosted by Rome Therapeutics and Enara Bio, two biotechnology companies working on translating our growing understanding of this vast genetic landscape into therapies for human disease. The spirit and ambition of the meeting was one of shared knowledge, looking to strengthen the network of researchers engaged in the field. The meeting opened with a welcome from Rosana Kapeller and Kevin Pojasek followed by a first session of field defining talks from key academics in the space. A series of panels, bringing together academia and industry views, were then convened covering a wide range of pertinent topics. Finally, Richard Young and David Ting gave their views on the future direction and promise for patient impact inherent in the growing understanding of the Dark Genome.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it