Bibliographic record
Abstract
As If, and: Ashes Margot Block (bio) As If I remember the length of my body as if it was beautiful and stillI dream this way in the moonlight you have sent meand that we are, we were wrong about everything [End Page 68] Ashes in the newspaperthere is a humanity that electrocutesour bending hearts they compromiseI saw the sun riseand I saw it in the ashes of every civilizationquietlyI loved you and never spoke of itI know the tenderness of every word is not enoughthat rainbows were dipped in blackthat we could not betray these secretslike children we tired the artistic strugglesthe many conversation it inspireswhile there is a vision of life and losswhere is the forgotten poverty you speak ofwhere are the beaten women you cannot forgetas the blood of my poem disappearsthe shallow waves recoveryou were beautifulwearing the largest of heartsno longer sufferingno longer beautifulas I spit out a narrow reflection [End Page 69] Margot Block margot block has been writing since the age of fourteen and has been published in many journals. She participated in the high school mentorship program with the Manitoba Writers Guild, working with Canadian poet Carol Rose. She won first prize in a poetry contest sponsored by the Writers Collective and an honorable mention in a poetry contest sponsored by the Lake Winnipeg Writers Group. Copyright © 2023 University of North Dakota
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.431 | 0.320 |
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".