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Record W32717168 · doi:10.1139/cjm-2020-0143

The Landscapes of the Sublime 1700-1830: Classic Ground

2013· book· en· W32717168 on OpenAlexvenueno aff
Cian Duffy

Bibliographic record

VenueCanadian Journal of Microbiology · 2013
Typebook
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsSublimeRomancePeriod (music)ScholarshipRomanticismNatural (archaeology)HistoryArt historyLiteratureArtGeographyAestheticsArchaeologyLawPolitical science

Abstract

fetched live from OpenAlex

"The Landscapes of the Sublime, 1700-1830" is a major new study of the place of the 'natural sublime' in the cultural history of the eighteenth century and Romantic period. Drawing on a range of scholarship on the eighteenth century and Romantic period, on the wider category of 'the sublime' in Western and European thought, and on the praxis of literary and historical exegesis, the book generates new cultural histories of the different species of the 'natural sublime' encountered by British and European travellers and explorers during the eighteenth century and Romantic period, including: the Alps; the Italian volcanoes, Vesuvius and Etna; the Arctic and the Antarctic; the deserts of central and southern Africa; and the universe being revealed by the new astronomy. (Publisher's description)

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.018

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.166
Teacher spread0.155 · 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 designNot applicable
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

Citations16
Published2013
Admission routes1
Has abstractyes

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