Purgatorial Passions: “The Ghost” (aka Wilfred Owen) in Owen’s Poetry
Bibliographic record
Abstract
A young man writhes on a humble cot, the darkness lying heavy, smothering him. In his mind’s eye a horse-drawn cart rumbles along a broken road. A heavy object strikes one horse and both bolt. Two figures catapult from the cart, one falling beneath the rear wheel, blood smearing the face. The wheel spins, inducing nausea in the sleeper, and then it is a bicycle wheel, dangling and bent, and seen from muddy clay. A fresh-dug grave sinks into the mud and the young man stands at its edge, scorning and mocking, and stabbing at the putrid air, as the words of his creed hang in it. As he falls forward, gray Gorgon-faced despair clutches at him … The sleeper cries out and sits bolt upright. His heart runs fast and irregularly, his dark eyes shrink back in his head. Shadowy phantasms swirl around him, bearing crosses, fingering his hair. He screams but nothing comes out and he chokes. His arm shoots up to ward off these ghosts, but he is thrown off balance, and falls to the floor, seeing nothing. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".