Space Squid Archives: Issues 1-9 and other materials (Texas A&M University Special Collections)
Bibliographic record
Abstract
This is the metadata record for the physical collection held at Texas A&M University's Cushing Memorial Library and Archives, as documented at https://findingaids.library.tamu.edu/index.php/issues-1-9-and-other-materials . Box 1 of the Space Squid archives Space Squid is an award-winning alternative literary journal publishing speculative fiction, experimental fiction, bizarro, and humor. Authors include Nicky Drayden (The Prey of Gods, Temper), Kelly Luce (Three Scenarios in Which Hana Sasaki Grows a Tail), Bruce Sterling (Holy Fire, Islands in the Net), Chris Roberson (Clockwork Storybook, Superman, iZombie), Jay Lake (John W. Campbell Award winner), Jennifer Pelland (Nebula nominee), Tony Millionaire (Maakies), and Caroline M. Yoachim. (1/10) Issue guide, written by Matthew Bey. (1/20) Space Squid, issues 1-4 (not numbered as such). (1/30) Master copy of no. 5. (1/40) Space Squid, issues 6, 8, 9. (1/50) Space Squid no. 6c, with photocopy. (1/60) Color master of no. 7. (1/70) Articles about clay magazine issue. (1/80) "Hunting Bigfoot" by Kevin Brown. (1/90) Ephemera. (1/100) Tales of Mushroom Men. (1/110) Space Squid no. 10. (1/12) Space Squid no. 11 (Summer 2012) (1/13) Space Squid no. 12 (Summer 2015) (1/14) Space Squid no. 13 - 14 (Summer 2016 - Summer 2017)
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.782 | 0.617 |
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".