Bibliographic record
Abstract
When I was younger I didn’t know a thing about death. I thought it meant stillness, a body gone limp. A marionette with its strings cut. Death was like a long vacation–a going away. Not this. \n \nStorms and flooding are worsening around the world, and a mysterious immune disorder has begun to afflict the young. Sophie Perella is about to begin her senior year of high school in Toronto when her little sister, Kira, is diagnosed. Their parents’ marriage falters under the strain, and Sophie’s mother takes the girls to Oxford, England, to live with their Aunt Irene. An Oxford University professor and historical epidemiologist obsessed with relics of the Black Death, Irene works with a Centre that specializes in treating people with the illness. She is a friend to Sophie, and offers a window into a strange and ancient history of human plague and recovery. Sophie just wants to understand what’s happening now; but as mortality rates climb, and reports emerge of bodily tremors in the deceased, it becomes clear there is nothing normal about this condition–and that the dead aren’t staying dead. When Kira succumbs, Sophie faces an unimaginable choice: let go of the sister she knows, or take action to embrace something terrifying and new. \n Tender and chilling, unsettling and hopeful, The Migration is a story of a young woman’s dawning awareness of mortality and the power of the human heart to thrive in cataclysmic circumstances.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.241 | 0.074 |
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".