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Record W3163738582 · doi:10.21083/csieci.v14i2.6459

Good Time to Plant Seed

2021· article· en· W3163738582 on OpenAlexvenueno aff
Dong-Won Kim

Bibliographic record

VenueCritical Studies in Improvisation / Études critiques en improvisation · 2021
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsnot available
Fundersnot available
KeywordsImprovisationHumanityCoronavirus disease 2019 (COVID-19)Value (mathematics)AestheticsEnvironmental ethicsHistoryArtPolitical scienceVisual artsLawPhilosophyComputer scienceMedicine

Abstract

fetched live from OpenAlex

Now we all know that the world and music environment won't be the same after the pandemic. Perhaps we have to define it as a crisis for musicians and performers. However, I'd suggest us to pursue the value of improvisation in bigger desperation. It's like when farmers lost their harvest for some reason, they always go back to the stage of planting a seed. I believe that improvisation becomes more valuable in the crisis because it always leads us to the most essential elements of artistry and humanity. We can start over from there. We have each other and technologies to keep us contacted.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0070.012
Scholarly communication0.0050.011
Open science0.0010.005
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0570.030

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 head0.036
GPT teacher head0.366
Teacher spread0.330 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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