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Epilogue

2015· book-chapter· en· W4242495975 on OpenAlexaboutno aff
Tom Beghin

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPianoArtPleasureReflexive pronounArt historyLiteraturePhilosophyClassicsPsychology

Abstract

fetched live from OpenAlex

When in 1829 the English musician Vincent Novello found a “Grand Piano Forte” “that belonged to Haydn,” he assumed that the reader would take the continuation of his story for granted: “I need not add that I sat down and played upon it with peculiar pleasure.”1Close What exactly Novello played, we’ll never know—and chances are he wouldn’t have thought it too important: what mattered was that, as he touched the keys the late master once played, he was able to transport himself back in time and breathe Haydn’s spirit—an experience enhanced by the physical presence of the Abbot Stadler, himself an éminence grise of what was rapidly becoming known as “the Viennese classical era.” When I traveled from Montreal to Belgium in 2004 to make a recording of Haydn’s three Accompanied Sonatas, Hob. XV:27–29, a set that Haydn wrote for the English pianist Theresa Jansen-Bartolozzi, I wasn’t quite sure what to expect. I had known and loved the circa 1798 Longman, Clementi, & Company piano that Chris Maene had restored not long before, an instrument that was similar if not structurally identical to the Longman & Broderip that Novello found in Stadler’s home. But Maene surprised us by announcing that he had constructed a brand-new version of it. I will never forget the moment when I saw both the skillfully restored original and its carefully cloned replica side by side, their juxtaposition creating a surreal reversal of the passage of time.

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)0.008
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.783
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.7830.517

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 head0.149
GPT teacher head0.238
Teacher spread0.090 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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