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Record W6994299345

Hybrid Bodies: PHI

2014· other· en· W6994299345 on OpenAlexaboutno aff

Bibliographic record

VenueePrints Soton (University of Southampton) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionWork (physics)Observer (physics)Transplantation
DOInot available

Abstract

fetched live from OpenAlex

Running at Montreal’s Phi Center, the exhibition Hybrid Bodies: An Artistic Investigation into the Experience of Heart Transplantation is a demonstration of such unmitigated collaboration. Launched in 2010 by a committed trans-disciplinary research team, across cardiology, philosophy, nursing, psychiatry, and sociology, practitioners invited four artists to work on the emotional and psychological impact of heart transplants on recipients. In this case, the remarkable innovation lies with the scientists, knocking at the door of the art world and going beyond mere dilettantism, as pointed out by UK participant Andrew Carnie in The Observer in 2002: “The practice of science is not isolated from the world we live in. Science has its politics, its economics, its fashions even. And anecdotally at least, some of the scientists involved in ‘sci-art’ collaborations report an intellectual engagement in them that goes further than personal enjoyment. It’s not just that it allows them to get out of their labs a bit more; it also seems to offer a different way of looking at their own work as scientists.” Exhibited works: Lacuna, A Change Of Heart, Heart and Mind Who is Knocking, A Tender Heart.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.220
Threshold uncertainty score0.737

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.006
Scholarly communication0.0090.006
Open science0.0010.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2200.022

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 head0.011
GPT teacher head0.196
Teacher spread0.185 · 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
Published2014
Admission routes1
Has abstractyes

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