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Record W7066632318

Improvised Music in Kingston

2023· other· en· W7066632318 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsImprovisationMusicalReading (process)Popular musicKey (lock)
DOInot available

Abstract

fetched live from OpenAlex

This Research-Creation project examines the experiences and music of a group of Kingston- based improvising musicians from across musical genres. The researcher participates in collaborative free improvisation inspired by questions of individual method, approaches toward playing in a group, and aspects of living in Kingston which may have impact on these experiences. Through interviews, live performance, and a series of podcasts, we learn about the lives of improvising musicians during the backdrop of the COVID-19 pandemic, from 2020 to 2023 in Kingston, Ontario, Canada. This reading is designed to supplement the full project (including music and podcasts) available at the Improvised Music in Kingston website (https://imik.netlify.app).

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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.310
Threshold uncertainty score0.616

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.007
Scholarly communication0.0050.001
Open science0.0010.011
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.003

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 head0.009
GPT teacher head0.184
Teacher spread0.175 · 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
Published2023
Admission routes1
Has abstractyes

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