How to clean a fish and other adventures in Portugal
Bibliographic record
Abstract
"How To Clean a Fish is an inviting family travel story about an extended stay in Portugal, full of food and cooking adventures, language barriers and bureaucracy, and that irresistible need to connect with the culture of our birth. After immigrating to Canada as a young child, Esmeralda Cabral remembers the initial shock--the weather, the wide and empty streets--and the immediate longing, saudade, to return to her homeland. That longing changed over time but never completely left. Cabral and her Canadian-born family had visited Portugal as tourists, but were now returning as residents for eight months, bringing along their Portuguese Water Dog, Maggie. Cabral has a deep desire to pass on her heritage to her children. By exploring the intricacies of adapting to a culture that is at once familiar and foreign, she reveals that the search for identity and belonging is a universal story. How to Clean a Fish will appeal to travellers and foodies, those curious about Portuguese culture, and to anyone who has moved from one place to another and is searching for their own version of 'home.'"--
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 | 0.000 | 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".