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Record W2504731265 · doi:10.1057/9780230282162_4

Portolans and the Late Medieval Transition

2010· book-chapter· en· W2504731265 on OpenAlexaff
Richard W. Unger

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2010
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTransition (genetics)HistoryAncient historyMediterranean climateClassicsArtGeographyLiteratureArchaeology

Abstract

fetched live from OpenAlex

The inability to understand the roots of those unique maps makes them even more mysterious as well as marvellous. They were also the first maps illustrated with ships, at first a few and then many and then very many. The portolano was no more than a list of sailing instructions. It stated simply the directions and distances between ports or prominent landmarks. There were no pretensions to detail or to literary quality. They were highly if not exclusively descriptive. Ancient Greece knew a very similar work. Few examples of the periplus have survived, the oldest being from the fifth century BCE and the latest from the fifth century. The last, by Marcianus Heraclensis, covered Europe to the mouth of the Vistula and was a compilation of earlier works, the typical pattern with all such books. The best known was the fourth century BCE compilation attributed to Scylax of Caryanda which covered the Mediterranean and adjacent seas. Though the material existed in such periploi to make a chart there is no evidence that one was ever made. The oldest surviving version of the book by Scylax is from the twelfth century so copies continued to be made. There seems to have been less of a Latin than a Greek tradition of writing such coast pilots.2

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.014
GPT teacher head0.193
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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