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Record W6995355444

Nest of Stone

2016· other· en· W6995355444 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of the Arts London Research Online (University of the Arts London) · 2016
Typeother
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsMovie theaterJuryAtmosphere (unit)Nest (protein structural motif)
DOInot available

Abstract

fetched live from OpenAlex

Nest of stone is a short animated film reflecting on death as a personal monument. 
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\n“The bleak and frosty atmosphere of a late autumnal day in a graveyard are pixelated in this narrated tale of recollection. The narrator weaves a sad tale as the inscriptions on the tomb stones trigger memories that she finds uncomfortable, as she gains acceptance of the nature of death and its place in life is pondered over and assessed reaching a satisfying conclusion.” (Steve Henderson in Skwigly Online magazine Animation)
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\nAwards
\n2015 Be There!, JURY PRIZE SHORT FILM Corfu, Greece
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\nOfficial selection
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\nWorld Premiere
\n2014 68th Edinburgh International Film Festival, Uk(BAFTA Qualifying Festival) 
\n2014 20th Encounters Film Festival, Bristol, UK (BAFTA Qualifying Festival & OSCAR Qualifying Festival)
\n2014 Aesthetica Short Film Festival, York, Uk (BAFTA Qualifying Festival)
\n2014 33th Vancouver International Film Festival, Vancouver, Canada
\n2014 Cinetekton Mexico
\n2014 Animated Dreams, Tallin, Estonia
\n2014 8th British Shorts Film Festival in Berlin, Germany
\n2015 Cinema Perpetuum Mobile International Short Film Festival, Minsk, Belarus
\n2015 w-o-l-k-e , Brussels, Belgium
\n2015 Biennale Women’s International Short Film Festival, Losone, Switzerland
\n2015 BioBioCine, Concepción International Film Festival, Chile
\n2015 Athens Animfest, Greece
\n2015 Be There!, Corfu, Greece
\nSpecial Screening & Retrospectives
\n2015 Rising Tides, London, UK

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.034
GPT teacher head0.303
Teacher spread0.269 · 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.

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
Published2016
Admission routes1
Has abstractyes

Explore more

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