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Record W2944719025 · doi:10.1162/leon_r_01760

<i>Movement, Action, Image, Montage: Sergei Eisenstein and the Cinema in Crisis</i> by Luka Arsenjuk. University of Minnesota Press, Minneapolis, MN, 2018. 280 pp., illus. Paper. ISBN: 978-1517903206.

2019· article· en· W2944719025 on OpenAlexaboutno aff
Will Luers

Bibliographic record

VenueLeonardo · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIconMovie theaterDownloadAction (physics)CitationState (computer science)Art historyMovement (music)ArtMedia studiesVisual artsComputer scienceSociologyLibrary scienceWorld Wide WebAesthetics

Abstract

fetched live from OpenAlex

June 01 2019 Movement, Action, Image, Montage: Sergei Eisenstein and the Cinema in Crisis Movement, Action, Image, Montage: Sergei Eisenstein and the Cinema in Crisis by LukaArsenjuk. University of Minnesota Press, Minneapolis, MN, 2018. 280 pp., illus. Paper. ISBN: 978-1517903206. Will Luers Will Luers the Creative Media Digital Culture Program. Washington State University Vancouver. Email: wluers@gmail.com. Search for other works by this author on: This Site Google Scholar Author and Article Information Will Luers the Creative Media Digital Culture Program. Washington State University Vancouver. Email: wluers@gmail.com. Online Issn: 1530-9282 Print Issn: 0024-094X ©2019 ISAST2019ISAST Leonardo (2019) 52 (3): 328–329. https://doi.org/10.1162/leon_r_01760 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Will Luers; Movement, Action, Image, Montage: Sergei Eisenstein and the Cinema in Crisis. Leonardo 2019; 52 (3): 328–329. doi: https://doi.org/10.1162/leon_r_01760 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsLeonardo Search Advanced Search This content is only available as a PDF. ©2019 ISAST2019ISAST Article PDF first page preview Close Modal You do not currently have access to this content.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.796

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)0.0010.000

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 head0.012
GPT teacher head0.224
Teacher spread0.213 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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