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Record W3005848279 · doi:10.33137/mt.v7i2.33674

Imagine It Thick In Your Own Skin: Sculptures and a Unique Artist’s Book

2020· article· en· W3005848279 on OpenAlexvenueno aff
Heide Hatry

Bibliographic record

VenueMediaTropes · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace Science and Extraterrestrial Life
Canadian institutionsnot available
Fundersnot available
KeywordsSculptureTragedy (event)ArtBeautyMeaning (existential)AestheticsIdentity (music)Visual artsGermanNatural (archaeology)Perspective (graphical)HistoryLiteraturePsychology

Abstract

fetched live from OpenAlex

In this artistic contribution, New York-based German artist Heide Hatry offers pictures of her sculpture series Imagine It Thick In Your Own Hair. According to Hatry, the project was intended to make people aware of the tragedy and motivate them to help clean up the disaster BP created in 2010 with the Deepwater Horizon spill. Hatry is best known for her body-related performances and her work employing animal flesh and organs, and cremated remains. Among her fundamental preoccupations are identity, death, the nature of aesthetic experience and the meaning of beauty, the effects of knowledge upon perception, the human exploitation of the natural world, and the social oblivion that permits atrocity to persist in our midst.

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 score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.003

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 head0.018
GPT teacher head0.256
Teacher spread0.238 · 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
Published2020
Admission routes1
Has abstractyes

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