Bibliographic record
Abstract
James Thunderstorm, a Blackfoot Native from Northern Ontario, travels to Montreal to pursue a college education. His girlfriend Madeline Swift doesn't want him to leave, citing her clairvoyant grandmother Ruth's prediction that James will die a horrible death in the city. Ignoring the warning, James arrives in Montreal. Once acclimated to the city, he becomes involved with a fellow student named Erica Frost. Then one night in Chinatown with his friends, James takes a hit of a mystery drug that replicates a near-death experience. Weeks later, he suffers nightmare flashbacks, particularly the recurring image of a demon. This image is used in the creation of a Halloween effigy by James and his friends at a party. Soon after, everyone involved in this creation suffers varying degrees of bad luck--some of it incidental, some of it fatal. James discovers that one of his friends is dealing out the near-death drug, infringing on the territory of criminal gangs in the process. James is dragged into the conflict against his will. He doesn't realize that the drug has caused a dangerous side-effect in his body. The visions he experienced--stemming from a previous life, according to a psychic--might manifest themselves in reality. Threatened by both the criminal underworld and an ancient spirit world, James is forced to confront it all.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.466 | 0.295 |
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".