Bibliographic record
Abstract
“The rise and fall of a chest, snores bellowing into the celeste, the sheep slowly realize they no longer need to jump into the dreamt sky, return to the barn to rest, no longer on their quest.” This is an excerpt from pages 5 and 6 of Dream Sheep, a story of the idiom to fall asleep by simply counting sheep, to slowly let them hop over the fence quelling you into a dreamful rest. Sleep for me started by being a kid, tucked into bed looking up at the ceiling where my dad would cover the big light with a book. These memories were what established the beginnings of this book. So many colorful pages shine through a few of the dark glimpses of what some nights of my sleep are in reality. For in truth, there are many nights of sobs, aches all over my body, and thoughts that seem to run for miles on end. My work focuses on both these aspects of sleep and how I still have a desire for sanctuary in sleep. Going into my childhood and recreating scenes of what would comfort me, I fully embrace counting sheep once more.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.265 | 0.194 |
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".