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Record W4380266032 · doi:10.1515/9780228013327

Out of the Studio

2022· book· en· W4380266032 on OpenAlexaboutno aff
John Osborne, Peter Smeaton

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2022
Typebook
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
Fundersnot available
KeywordsStudioComputer graphics (images)ArtComputer scienceVisual arts

Abstract

fetched live from OpenAlex

Photography, one of the most influential inventions of the nineteenth century, has been shaped by Canadian innovators. Among them are two Quebec men who have flown beneath the radar in studies of the history of photography: the Smeaton brothers. Out of the Studio documents the life, oeuvre, and achievement of Charles Smeaton and his younger brother, John. Launched by the opening of their “photographic gallery” in 1861, they developed a reputation in Quebec for images of contemporaneous people, places, and events taken in challenging outdoor settings. Smeaton pictures of the aftermath of the Great Fire of Quebec in 1866 helped bring an understanding of the disaster to an international audience; images featuring the gold mining industry were displayed at the Exposition universelle in Paris the following year. When Charles travelled to Europe in 1866, he accomplished a feat previously thought impossible, taking the first successful photographs in the Roman catacombs. John moved to Montreal in 1869, where he worked for newspapers and developed techniques for the direct transfer of photographs into print without the necessity of intermediary engravings. Out of the Studio is the first comprehensive biographical study detailing the innovation and imagination of the Smeaton brothers and their legacy of images across two continents.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.288
Threshold uncertainty score0.963

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.002
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.2880.106

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 head0.032
GPT teacher head0.217
Teacher spread0.185 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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