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Record W4408567716 · doi:10.3138/cart-2024-0029

Are Portolan Charts and Portolan Mile Geometrically Rooted in Classical Antiquity? A Cartometric Analysis of al-Shirazi’s “Greek Map” and the <i>Pisane, Lucca, Avignon</i>, and <i>Cortona</i> Charts

2024· article· en· W4408567716 on OpenAlexvenueno aff
Tome Marelić

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHistorical Astronomy and Related Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMileArtGeographyAncient historyHistoryCartographyGeodesy

Abstract

fetched live from OpenAlex

Some of the earliest-made known portolan charts ( Pisane, Cortona, Avignon, and Lucca charts) and Qutb al-Din al-Shirazi’s schematic (1282) resembling “a map of the Mediterranean that was drawn by the sages of Greece and the ancient geometers” were cartometrically analysed. The results show that the Mediterranean was drawn nearly identically on the Carte Pisane and Lucca chart and that the preserved fragment of the Avignon chart is somewhat of an intermediate step between the Pisane–Lucca model and Pietro Vesconte’s model. The coasts of al-Shirazi’s schematic fit well with the Pisane and Cortona charts, whereas its 40×30 grid is similar in size to the grid drawn on the Pisane and Avignon charts. The length of its sides along the latitude φ = 36° (125 km) corresponds to 100 portolan miles ( miglia) and a 2-degree interval along the parallel φ = 36° according to Ptolemy’s incorrect estimation of the Earth’s size. Hypothetically, such a misunderstanding could have occurred if a late medieval cartographer (unfamiliar with the differences between spherical and Euclidean geometry) erroneously combined different spatial datasets from classical antiquity by unwittingly superimposing Ptolemy’s longitudes onto maps or charts made according to Eratosthenes’s correctly obtained size of the Earth by treating them as distances.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.261
Teacher spread0.254 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCartographica The International Journal for Geographic Information and GeovisualizationSame topicHistorical Astronomy and Related StudiesFrench-language works237,207