P-41 Documentation of William Huber, Jr. Collection at The Library of Congress and Its Namesake; Musical Composition Fostering and Efficiency Project
Bibliographic record
Abstract
In June 2015 I travelled to a rural part of British Columbia, Canada for the express purpose of creating music within its highly-conducive environment, an aspect of my AU FRG-sponsored activity. I composed mostly outside, sitting in a pasture with an ebb-and-flow of some 30 alpacas and three horses, often pausing to soak in the inspiring environment and to exercise (including bicycle riding in the pasture). On average, I composed for approximately 55 hours per week for about three weeks. This process was extraordinarily productive (even while mostly done less efficiently with pencil and paper instead of with computer and keyboard), yielding drafts of approximately two dozen new musical works. The major aspect was creating musical drafts for the There Is set of four anthems for SAB voices and organ, which have been edited, computer entered, and submitted for publication consideration. Overall, I wrote for several choral combinations (Soprano I/Soprano II/Alto I/Alto II, for example), with some emphasis on texts by Christina Rossetti. Finally, I drafted two organ solo compositions anticipating my participation as organist in the 2015 General Conference Session.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".