Bibliographic record
Abstract
This poster has been presented at the Music Encoding Conference 2022 at Dalhousie University, Halifax, Canada. It shows the history of MerMEId from its beginning in 2009 until 2022. The “Metadata Editor and Repository for MEI Data” (MerMEId) is a web based tool to capture and enrich data in the MEI header. The tool was originally developed by Axel Teich Geertinger and Sigfrid Lundberg at the “Danish Centre for Music Editing” for their own work on the thematic-bibliographic catalogues of works of Carl Nielsen, Johann Peter Emilius Hartmann, Johann Adolph Scheibe, and Niels W. Gade (Teich Geertinger & Pugin, 2011; Teich Geertinger & Lundberg, 2015). From the beginning—around 2009—the development of the MerMEId was tightly connected to the evolvement of the MEI standard and the editor was presented at numerous occasions. For 2022 the release of MerMEId 2.0 is planned, introducing new features which were implemented in a community effort. Teich Geertinger, A., & Pugin, L. (2011). MEI for bridging the gap between music cataloguing and digital critical edition. In <em>Die Tonkunst,</em> 5 (3), 289–294. Teich Geertinger, A., & Lundberg, S. (2015). MerMEId: Creating Thematic Catalogues Using MEI Metadata. In Roland, P., & Kepper, J. (Eds.), <em>Music Encoding Conference Proceedings 2013 and 2014</em>. Bavarian State Library (BSB), 122–126. URN: http://nbn-resolving.de/urn:nbn:de:bvb:12-babs2-0000007812.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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; both teacher heads agree on what is shown here.
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".