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Record W2990948235 · doi:10.5117/9789463729000_ch07

The Fog Medium: Visualizing and Engineering the Atmosphere

2021· book-chapter· en· W2990948235 on OpenAlexaff
Yuriko Furuhata

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicVisual Culture and Art Theory
Canadian institutionsMcGill University
Fundersnot available
KeywordsMovie theaterVisibilityHazeVisual artsArtHistoryMedia studiesMeteorologyGeographySociology

Abstract

fetched live from OpenAlex

Yuriko Furuhata explores the fog sculptures of artist Nakaya Fujiko. Nakaya’s deployment of fog and smoke recalls other expanded cinema practitioners and environmental artists in the postwar period, yet her experiments take on a different significance when seen not as a descendant of the phantasmagoria but as part of an assemblage linked to the development of smoke screens for aerial warfare. Paying particular attention to the dual function of fog screens—which obfuscate visibility yet also make visible such qualities as temperature, humidity, and wind—Furuhata historicizes the epistemological and political conditions behind the turn to fog and smoke within expanded cinema and the environmental arts during the Cold War. In so doing, Furuhata provides a geopolitically nuanced twist to the recent interest in ‘atmospheric media’ and ‘elemental media’.

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.223
Teacher spread0.199 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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