Bibliographic record
Abstract
Self-Study with Assorted Shadows Todd Copeland (bio) I follow my long shadow,running down a stretch of rural roadin a marathoner's tranceunder July's indiscriminate sun. Lux est umbra Dei, the ancients said. My shadow, then, twice-removedfrom pure illumination. I cast myselfas Everyman, companionless and peregrine,a runner for years and stillnowhere near anything of notethough I catalogue my stepsas if they were aimed towardsome Ultima Thule of our age. Trading in solitudes and silences,a taste of salt in my dry mouth,why hope to find beatitudechasing after my body's dark star? Flushed from a windbreak,birds sweep low over a field of sorghumready for harvest—black doorsto the bronze intricacies of summer. [End Page 587] Todd Copeland Todd Copeland's poems have appeared in The Journal, High Plains Literary Review, Southern Poetry Review, Valparaiso Poetry Review, Sewanee Theological Review, The Dalhousie Review, and Columbia Poetry Review, among other publications. A native of Ohio, he currently resides in Waco, Texas. Copyright © 2020 Todd Copeland
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".