Bibliographic record
Abstract
The Digital Splitleaf Psalter uses Verovio (verovio.org),a lean, portable, opensource library of code, to produce a clear, easy to read musical score from a JavaScript merger of text and musical notes.The tool addresses a perennial problem for many historic song repertoires: finding a suitable tune from many possible options for a particular song lyric.This particular tool looks at metrical psalms, in which the lyric form uses a strict number of syllables in lines, and lines in recurring verses.Theoretically, it might be possible to develop such a tool for other kinds of fixed-form lyrics, although for now, the Digital Splitleaf Psalter provides those interested in historic psalmody, as well as those actively using this repertoire in regular worship, with a useful portal to integrate words and music.This project is timely, as a quick survey of the past couple hundred years shows that generations of users (and here, I really mean biologically rather than technologically defined generations) have been looking for usable solutions in this area.In recent years, there have been other projects that have presented users with packages of psalmody using modern editions of psalters and hymnals, with static links to MP3 and image files.While these can be useful archives, what they present reflects the perspective of the website designers and a contemporary framework for reading the material.Conversely, what Timothy Duguid brings to the Digital Splitleaf Psalter project is both expertise in digital technology and knowledge of the authoritative historic sources, allowing a user to steer their own course through the material using the historical structures more directly.Duguid currently works in digital humanities at the University of Glasgow and was the research associate for the University of Edinburgh project Singing the Reformation.That project created both recordings of and modern singable scores for the contents of the sixteenth-century manuscript collection known as the Wode Psalter.The fruits of this work are now available from the Church Service Society (churchservicesociety.org/str/about-singing- reformation-2016), presented using the sort of static link archive discussed above.Duguid has also published an authoritative monograph comparing the early English and Scottish psalters, so his understanding of the printed
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.461 | 0.392 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".