Bibliographic record
Abstract
"As it is inked, so shall your oaths and bindings be." Tattoos are the only law on the Island of the Free, and there can never be a king. Every clan agrees on that. But a returning exile has smuggled something across the water that could send the old ways up in flames. Elias wants revenge on the men who severed his oaths and made him an outlaw. But, if his wealth and honour are to be restored, he’ll need help from the most unlikely quarter – a mysterious woman, landed unwontedly on Newfoundland’s rocky shore. "I love that these are great adventure stories, but also have a more thoughtful side to them – the worlds we visit are all very different and flawed in very different ways, but inhabited by people who have been shaped by the nature of those worlds. It’s very clever, but also very engaging – I find myself completely drawn in, unable to predict what will happen next. I also have a strong sense that there is an overall plan to the whole series – this is building into a fantastic overall tale. Really looking forward to the next instalment!” – Clare Littleford, author of The Quarry
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.016 |
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".