Bibliographic record
Abstract
The following description is provided by the publisher: <br> FICTION <br> “Bodies in the Lake” by Bev Craddock <br> “Butterfly on a Mountain” by Mark Anthony Jarman <br> “Devil’s Lake” by Astrid Blodgett <br> “One We Could Stand to Lose” by Kevin Hardcastle <br> “Syzygy” by Laura Legge <br> NON-FICTION <br> “Happy Hour” by Karen J Lee <br> “Through the Rockies” by Jody Smiling <br> POETRY <br> “Layover” by Patrick Grace <br> “Kananaskis (Can I Ask This?) ” by Jessica Saunders <br> “My Montreal Vagina,” “Petrified,” and “Red Mailboxes” by Billeh Nickerson <br> “Shame” by Nabil Boschman <br> “Love as an Orange” by Michael Prior <br> “Shaken by Want” and “Sonnet LX” by Amy Wright <br> “I Love Hard Girls” by Leah Lakshmi Piepzna-Samarasinha <br> “Love Poems Don’t Work” by Andrew King <br> “Hook & Eye” by Jessica Rae Bergamino <br> “Puella” by Miki Fukuda <br> TRANSLATION <br> “My villanelle is just a stroke of luck” and “My villanelle was written by a creep” by Ariella Jenkins <br> Spanish by Ezequiel Zaidenwerg <br> COVER IMAGE <br> Human Heart Angiogram by Science Source Images
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".