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Record W2520510724 · doi:10.3138/cart.51.3.3569

Unifying Prospects: Tinting Geological Maps in Nineteenth-Century Britain

2016· article· en· W2520510724 on OpenAlexvenueno aff
Allison Ksiazkiewicz

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsnot available
Fundersnot available
KeywordsGeologistDepictionRepresentation (politics)SimplicityGeologyGeologic mapArchaeologyFeature (linguistics)HistoryPaleontologyArtVisual artsPhilosophyEpistemologyLinguistics

Abstract

fetched live from OpenAlex

Geologically interested savants of the late eighteenth and early nineteenth centuries described three-dimensional spatial relationships through the visual language of maps and sections of the Earth. At this time, there was a debate whether colour or line should feature in mapping our strata. Colour was an identifying characteristic of Wernerian mineralogy, but the exact manner in which colour should be employed in representing a mineralogical landscape remained controversial. According to the engineer and geologist William Smith (1769–1839), words or symbols, engraved on a map, marred a visual simplicity that accommodated an immediate understanding of the area represented. Colour enabled a quick and rational study of the countryside so that the savant instantly visualized the logic of the landscape. André-Jean-Marie Brochant de Villiers (1792–1857), professor of geology and mineralogy at École des Mines, argued differently. In a letter to Thomas Webster (1773–1844), he remarked on the difficulty of correlating colours in the key with those of strata when studying Greenough's Map of England and Wales (1819). By examining techniques of representation and the use of colour, this paper discusses the importance of aesthetics in the depiction of geological landscape.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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 designNot applicable
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

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCartographica The International Journal for Geographic Information and GeovisualizationSame topicHistory of Science and Natural HistoryFrench-language works237,207