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1,001 handshakes

2023· article· en· W4403734158 on OpenAlexaffabout
François‐Joseph Lapointe

Bibliographic record

Venue.able. · 2023
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

I inhabit the microbial world. Microbes live on my body and inside my body. Every opening in my body envelope is populated by millions and millions of different microbes. I eat microbes, swallow microbes, digest microbes, and defecate microbes. When I kiss my wife, I share microbes with her. When I shake hands with my neighbor, we swap our microbes. We are both part of a complex network of microbes commonly referred to as the microbiome, which is an essential part of our individual and collective bodies. The composition of my microbiome fluctuates on a daily basis, according to my all my actions and encounters. Although my genome is fixed, my microbiome is changeable and adaptable. I can transform my microbiome as I wish to change my identity. As part of my artistic practice, I expose my own body to various types of experiments aimed at changing the makeup of my microbiome. I then use the tools of science to quantify the effects produced. On February 3, 2016, I shook hands with 1,001 people at the Berlin Transmediale, gradually transforming the invisible community of microbes living in the palm of my right hand. At regular intervals, assistants took samples of this skin microbiome to study how contact with others transforms who we are. Since then, I have repeated this hybrid project, at the interface of art and science, in Copenhagen, Montreal, Perth, San Francisco, Baltimore, and Paris. The performance of 1,001 handshakes raises awareness through physical engagement, through acts of participation and exchange at the social, individual, and microbial levels. As a scientist, the objective of this experiment was to collect scientific data on the human microbiome, the dynamics of contamination of my microbiome in contact with the microbiome of others. As a bioartist, it was more the notion of individuality that appealed to me, a philosophical concept that I formalize through microbiome self-portraits, or microbiome selfies generated from the DNA of bacteria harvested from the palm of my hand. Hidden beyond the visible, in the palm of a hand, as the most curious visitors zoom in, these microbiome selfies reveal themselves on a micro scale. Am I still the same after a thousand handshakes with strangers? These multicolored bacterial networks attest to my metamorphosis. This mundane action of the handshake comes to us today in a new light amidst a global pandemic exacerbated by social distancing. The limits of my body are not those of my skin. I touch therefore I am. I carry traces of your microscopic identity with me. I am a network of microbial cells that dance with my own cells to construct the person that I am in real time.

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 categoriesInsufficient payload (model declined to judge)
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 score0.511
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.243
Teacher spread0.219 · 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
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
Published2023
Admission routes2
Has abstractyes

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