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Record W2278897983

Experimental music for experimental physics

2014· article· en· W2278897983 on OpenAlexaboutno aff
Rosaria Marraffino

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2014
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsTheoretical physics
DOInot available

Abstract

fetched live from OpenAlex

Using the sonification technique, physicist and composer Domenico Vicinanza paid homage to CERN at its 60th anniversary ceremony. After months of hard work, he turned the CERN Convention and LHC data into music. Click here to download the full score of the "LHChamber music". Every birthday deserves gifts and CERN’s 60th anniversary was no exception. Two gifts were very special, thanks to the hard work of Domenico Vicinanza, a physicist and composer. He created two experimental pieces by applying the sonification technique to the CERN Convention and to data recorded by the four LHC detectors during Run 1. “This technique allows us to ‘hear’ data using an algorithm that translates numbers or letters into notes. It keeps the same information enclosed in a graph or a document, but has a more aesthetic exposition,” explains Domenico Vicinanza. “The result is meant to be a metaphor for scientific cooperation, in which different ‘voices’ and perspectives could reach the same goal only by ‘playing’ together.” Each source of data could be sonified in many ways, which is where the genius of the composer comes in: “I chose how to map the data to musical parameters since, as with any composition, I had to make decisions concerning the choice of the scale, the instruments, which instruments play when, timbre, tempo, etc.,” says Vicinanza. “I created different melodic lines but the magic happened when all the instruments played together. The same applies to scientific research, where support and cooperation allow great results to be achieved.” The Convention has more than 28,000 characters, and each one was translated into a note: same letter, same note. The algorithm didn’t do all the work; the human element of the creative process was essential: “It took me more than 250 hours to sonify the Convention, but I really wanted to celebrate what it really means: peace beyond any political disagreement, for the common purpose of scientific research,” explains the composer. During the 60th anniversary ceremony, the European Union Youth Orchestra* directed by Maestro Vladimir Ashkenazy, played Domenico Vicinanza’s sonified Convention, so he had to write the score for each instrument. "The orchestra kindly accepted to extend their membership, which originally represented the 28 EU Member States, to 42 young players covering all of CERN’s Member States and Observers in order to convey the message of harmony and peace that they share with our Organization" says Paola Catapano of CERN’s Communications Group, co-producer, with Vicinanza, of the EUYO performance. For the LHChamber music, seven instruments were recorded in the four experimental caverns and in the CERN Control Centre. “Scientists played the music from the data they had worked on in the places where they actually worked,” explains Vicinanza. “Every instrument had its own sense, like the research they did, but only when they’re played together do you feel the harmony in it: it’s like the whole goes beyond the sum of the parts. Writing the scores out of these data made me feel like the musical alter ego of a researcher.” * Click here to download the mp3 recording of the European Union Youth Orchestra. Did you know? “If the Large Hadron Collider made music, what would it sound like?” read the title of an article in The Guardian on 30 September featuring the “LHChamber Music” video. This was just one of 36 online media sources across the world, including the UK, China, India, the US, Italy, France, Canada and even Palestine, that reported on CERN’s You Tube video between September 29 and October 4, reaching a combined readership of more than 198 million people! With hits on the YouTube video growing from 9000 to over 20,000 views in under 24 hours and reaching over 50,000 in one week, the video is definitely CERN’s most successful in 2014 and among the top ten ever published on the CERN YouTube channel. “LHChamber Music” went viral on Twitter too: the phrase “CERN music” was tweeted 1147 times in nine days by 1039 contributors, including unexpected CERN supporters such as the UK’s Royal Philharmonic Society!

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)0.005
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.223
Threshold uncertainty score0.745

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.006
Scholarly communication0.0090.010
Open science0.0020.007
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.2230.094

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 head0.037
GPT teacher head0.280
Teacher spread0.243 · 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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