Bibliographic record
Abstract
Carnage James Owens (bio) The weasel knew their warmth in the dark,ripped throats, let drop the gangly, earnest bodies of two-week-old domer chickswe found slain in the obvious morning light, the chicken coop an aftermath, an abattoir,blood-sopping tufts of down scattered awry, forty-eight of fifty dead, the two living birdshuddled in a corner, heads under their wings. My tender mother falls to her knees,her grief instant and helpless and universal. She can’t erase their fear in those jaws.My father tries what he cannot do, beside her on the dew-beaded grass,arms around her heaving shoulders, promising more chicks, a better coop,saying her name, touching her face, both of them uncomprehending and bloodied,words too frail in the gap as she pulls away. [End Page 95] James Owens James Owens’s most recent collection of poems is Mortalia (FutureCycle Press, 2015). His poems, stories, and translations have appeared widely in literary journals, including publications in The Fourth River, Kestrel, Pikeville Review, Poetry Ireland Review, and Southword. Originally from Southwest Virginia, he worked on regional newspapers before earning an MFA at the University of Alabama. He lives in Indiana and northern Ontario. Copyright © 2018 Berea College
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.776 | 0.540 |
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".