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Record W2782057403 · doi:10.7238/a.v0i20.3140

INCUBATOR Lab: Re-Imagining our Biotech Future Through Art / Science Research

2017· article· en· W2782057403 on OpenAlexaffabout
Jennifer Willet

Bibliographic record

VenueArtnodes · 2017
Typearticle
Languageen
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsIncubatorPremiseWindsorThe artsEcologySociologyEngineering ethicsEngineeringVisual artsArtBiologyEpistemology

Abstract

fetched live from OpenAlex

INCUBATOR: Hybrid Laboratory at the Intersection of Art, Science and Ecology, is a bioart research and teaching facility housed in the School of Creative Arts at University of Windsor in Canada. Founded in 2009 by Dr. Jennifer Willet, INCUBATOR houses ongoing student and faculty bioart projects, science and technology studies research, and special events investigating the intersection of biotechnology, art and ecology. This paper traces for readers the fundamental conceptual premise of INCUBATOR lab activities, the complex ecological entanglement between contemporary laboratory practices and our planetary ecology as a case study to elucidate the research/creation process at play within the lab.

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)0.009
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.993
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.026
Scholarly communication0.0130.014
Open science0.0010.011
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.339
GPT teacher head0.581
Teacher spread0.242 · 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.

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
Published2017
Admission routes2
Has abstractyes

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