Jeff Schnader: 47th Annual ODU Literary Festival
Bibliographic record
Abstract
Jeff Schnader is an author living in Norfolk, Virginia. His novel, The Serpent Papers, published by The Permanent Press, is about the turbulence in America during the Vietnam War. The book won 2nd Place in the 2023 Independent Authors Network’s Grand Prize for Fiction of the Year and 1st Place in Outstanding Historical Fiction. It was also the Bronze Winner in the Foreword Reviews Book of the Year Awards. Nominated for a Pulitzer, it was also named “Finalist” in several other competitions. His short story, “The Champion,” won 1st Prize in the LUW Quills Awards. His short stories and essays have been published widely, and he has been interviewed on radio across the U.S. and in Europe. He has just completed his second novel, Star Chamber, for which he seeks representation. Previously, he was a physician and Professor of Medicine, having graduated from Columbia, McGill, and Johns Hopkins. He has been a medical journal editor, research scientist, and ICU director, authoring 50 medical publications.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.101 | 0.031 |
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".