Bibliographic record
Abstract
After the Vet's Diagnosis, and: When I Move from This House Laura Sweeney (bio) After the Vet's Diagnosis Maybe a heart tumor the vet said of my dog Freya's dry hack and gasping for air, yet my memory of that day is how we played in Carterville's Canon Park, that place those hours, divined in autumn's golds and reds. The diagnosis seemed impossible, as if Freya knew, defied her battle. Only happens to the good ones the vet said yet Freya bounded into that crisp autumn air as if to prove the vet's diagnosis impossible, the strain of this is serious fading into memory as we explored the paths until we both glowed red. I lost count of our laps around that place as we circled the fields and hedges 'til our normal emerged rather than the battle's raging head. Freya led me into the garden's lavenders and reds then onto the deck where I savored the lake air and the white noise of the fountain, memories like leaves floating when Freya proved her healing possible. Then she led me under the canopy of trees, possibly to find a soccer ball, feisty, inexhaustible, as if to prove look mom all will be well, her determination filling the flush of sunset's fading red. And yet another lap under the lampposts where once we read an art display of fairytales. Palms raised to the air, I prayed knowing full well it's not a fairytale this battle and reciting lyrics from songs that have carried loved ones through like Helen Reddy's "You and Me Against the World." I heard on the radio of her dementia battle, reminding healing is not always possible. Loved ones move on leaving those behind to carry on amongst the autumn reds. yet while tomorrowmay bring ashes today webrightly burn this air . . . (September, 2020) [End Page 71] When I Move from This House this house with the woodpeckers who wake me,I will pack the skink's electric blue tail. Sometimes he naps on my stoop sunbathing.And I will pack the mud daubers who built organ pipe nests in my garage doorway.Even the field mice, six I caught in traps. And camel crickets too. And by the waymy Freya monster doxie I'll pack last. She looks up at me already knowingas she knows when we're in Evergreen Park our first village at this university.The grin she gave me I will also pack, pleased after years of moving for this yard,twirling under the maple tree's propellers. (700 Billy Bryan, Carbondale, IL, July 2021) [End Page 72] Laura Sweeney laura sweeney facilitates Writers for Life in Iowa and Illinois. She represented the Iowa Arts Council at the First International Teaching Artist's Conference in Oslo, Norway. Her poems and prose appear in sixty plus journals and ten anthologies in the States, Canada, Britian, Indonesia, and China. Her recent awards include a scholarship to the Sewanee Writer's Conference. She is a PhD candidate, English Studies/Creative Writing, at Illinois State Unviversity. Copyright © 2023 University of North Dakota
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.232 | 0.109 |
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".