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Record W2804297325 · doi:10.5194/ica-proc-1-67-2018

Chinese Mapped America Before 1430

2018· article· en· W2804297325 on OpenAlexfundno aff
Siu-Leung Lee

Bibliographic record

VenueProceedings of the ICA · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geography and Cartography
Canadian institutionsnot available
FundersPhysicians' Services Incorporated Foundation
KeywordsMercator projectionGeographyChinaLongitudePeninsulaLatitudeCartographyArchaeologyGeodesy

Abstract

fetched live from OpenAlex

Abstract. Qualitative and quantitative comparison of Kunyu Wanguo Quantu (the 1602 Chinese world map) and contemporaneous world maps by Mercator (1569), Ortelius (1570) , Mercator’s Arctic map (1595), and Plancius (1594) in particular, reveals that the Chinese map is not an adapted copy from European maps. The Chinese world map includes geography of a pre-Renaissance Europe and American geography unknown to Europeans until more than 200 years after Ricci’s death. Approximately 50 % of the place names, including those of America, have no equivalents on European maps. Chinese names descriptive of the geographic feature of California peninsula, Mount Ranier, the fjords of Alaska, Mount Denali, tidal bore near Anchorage are all accurate by latitudes. Chile and Peru are correct by relative longitude. Contrarily, the maps by Plancius and Mercator are erroneous and ambiguous on the geography of North and South America. The geography and text of the Chinese world map are consistent with a completion date of 1430, some sixty years before Christopher Columbus’ first voyage. Martino Martini’s Novus Atlas Sinensis (1655) is not a survey of his own but translated from Chinese sources, revealing that Ming China was capable of determining longitude/latitude on land and ocean, as well as spherical projection. In conclusion, information about American geography was transferred from China to Europe, not the reverse. The Chinese world map Kunyu Wanguo Quantu is the result of Chinese circumnavigation and survey, pioneering the Age of Exploration, overturning 600 years of misinterpreted history.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.159
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.009
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.001

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 head0.006
GPT teacher head0.261
Teacher spread0.255 · 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
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

Citations1
Published2018
Admission routes1
Has abstractyes

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Same venueProceedings of the ICASame topicHistorical Geography and CartographyFrench-language works237,207