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Record W4386362399 · doi:10.1386/mms_00102_2

Editorial

2023· editorial· en· W4386362399 on OpenAlexaboutno aff
Nelson Varas‐Díaz, Nedim Hassan, Ross Hagen, Niall Scott

Bibliographic record

VenueMetal Music Studies · 2023
Typeeditorial
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBattleAppropriationSection (typography)Visual artsSymphonyStadiumHistoryMedia studiesArtArt historySociologyArchaeologyAdvertisingPhilosophy

Abstract

fetched live from OpenAlex

Issue 9.2 sees the light following an active summer for the field of metal music studies. During 6–9 June 2023, the International Society for Metal Music Studies held its 6th Biennial Research Conference in Montreal, Canada. The event was organized by Dr Vivek Venkatesh and his team at Concordia University. The issue’s main section includes five articles addressing the topics of stadium rock, the identity construction of famous metal guitarists, the idea of heaviness, symphonic metal’s appropriation of the Baroque, and the creation of a metal scene in Bandung, Indonesia. The issue includes reviews for books on references to Nazism in popular music, the visual dimensions of metal battle jackets, and Mercyful Fate’s 1984 album Don’t Break the Oath.

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)0.004
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.886
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.002
Science and technology studies0.0050.002
Scholarly communication0.0100.005
Open science0.0030.002
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.1140.109

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 head0.192
GPT teacher head0.294
Teacher spread0.102 · 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
GenreEditorial

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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