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Record W4402996623 · doi:10.56397/saa.2024.09.03

Aesthetic Study of Spatial Design in Denis Villeneuve’s Films

2024· article· en· W4402996623 on OpenAlexaboutno aff
Chengfang Chen

Bibliographic record

VenueStudies in Art and Architecture · 2024
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Visual Art
Canadian institutionsnot available
Fundersnot available
KeywordsArtAestheticsArchitectural engineeringArt historyEngineering

Abstract

fetched live from OpenAlex

Canadian director Denis Villeneuve has carved a distinctive niche in the realm of science fiction cinema with his unique spatial design aesthetics. This paper examines his directorial works including Dune, Blade Runner 2049, and Arrival, exploring how he intricately reveals complex relationships among human emotions, societal structures, and future technologies through natural landscapes, architectural styles, and narrative temporality. Natural landscapes serve not merely as backgrounds but as profound mediators of emotional dialogue with characters. Architectural styles not only align with world-building but also embody technological practicality and functionality. Narrative temporality, employing non-linear structures, deepens inner struggles of characters and exploration of destiny. Villeneuve’s films dazzle not only visually but also provoke profound contemplation on human existence and cosmic significance.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.040
GPT teacher head0.320
Teacher spread0.280 · 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 designOther design
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

Citations0
Published2024
Admission routes1
Has abstractyes

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