Bibliographic record
Abstract
The following description is provided by the publisher:<br> CONTENTS<br>NON-FICTION<br> Vinh Nguyen 79 Waiting, Resolution<br> FICTION<br> Kellv Pedro 7 People Are Not That Honest<br> Robert McGill 18 Your Puppy Meets the World<br> Dylan Fisher 24 The Boys<br> Candice May 39 Dad as House<br> Alison Stevenson 56 In the Garden<br> Jeremy Colangelo 67 Consolation of the Cat-Sitter<br> POETRY <br> Anne Baldo 14 the secrets of monsters<br> Sage Ravenwood 16 Triskaidekaphobia<br> Glenn Shaheen 22 Jumping from High Places in Twelve Open World Video Games<br> Pauline Peters 23 In the Garden of Remembrance<br> Sarah Yi Mei Tsiang 36 Walking on Water<br> Katie Marti 37 photo album ('79)<br> Saya Watanabe 51 Earthquake<br> Ruby Hansen Murray 54 Goodness!!<br> Kiala Löytömäki 65 This Too, Is a Type of Love<br> Jessica Le 73 Breakfast at T&T<br> Alison Braid 75 Fear of Desire nina jane drystek 76 late hibernal<br> Dominik Parisien 78 naming a plant after the dead<br> Contributors 90
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".