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Record W3156973091

Symphonic Victimae Paschali Laudes

2019· dissertation· W3156973091 on OpenAlexfundno aff
Henrique Coe

Bibliographic record

VenueTSpace · 2019
Typedissertation
Language
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsSymphonyArtLiterature
DOInot available

Abstract

fetched live from OpenAlex

Symphonic Victimae Paschali Laudes is a work for full orchestra based on the Gregorian chant Victimae Paschali Laudes. The composition is approximately 14’40’’ long and fuses elements of early music (Gregorian chant, organum) and contemporary music (use of extended instrumental techniques, coloristic textures). After a serene Introduction (mm. 1-28) bringing the first notes of the Gregorian chant over harmonics on the strings, the first phrase of the Gregorian chant is presented (mm. 29-43), followed by a harmonic transition and a hectic bridge (mm. 44-75) leading to the presentation of the second phrase of the Gregorian chant (mm. 76-116). Then, sections using ideas from the beginning as well as new ideas take place (mm. 117-330), starting with melodic material from the bridge combined with “intriguing” chords fading in and out. The two first phrases of the Gregorian chant reappear with variations and over different orchestral textures. New melodic material also ensues, and the “intriguing” chords reappear bringing tension. The tension is resolved with the reappearance of the Gregorian chant (mm. 331-end), which now is stated entirely—not only the two first phrases—into a maestoso character, with parallel fifths over pedal notes within a varied orchestration. The final measures of the work (375-end) are based on the words “amen” and “alleluia”. The composition ends in a grandiose but serene manner.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.031
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0310.012

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 head0.027
GPT teacher head0.313
Teacher spread0.286 · 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
Published2019
Admission routes1
Has abstractyes

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