Bibliographic record
Abstract
Resumo Na primeira parte deste artigo, mencionamos as obras do escritor alemão Georg Büchner (1813-1837), considerando especialmente o drama Woyzeck. Ressaltamos a novidade temática e estética dessa peça, pioneira em apresentar um homem despossuído no papel principal, obra com a qual Büchner se converteria em precursor de naturalistas e expressionistas. Nas seces finais, abordamos as razões para compor a peça Zé, adaptação em verso e canções de Woyzeck. O verso pode conferir ao texto certas qualidades musicais, as quais ampliam o campo de significações da peça teatral. Exemplos tomados a Zé são utilizados para expor tais hipóteses. Abstract In the first part of this article we mention the works of the German writer Georg Bu?chner (1813- 1837), especially considering the drama Woyzeck. We emphasize the aesthetic and thematic novelty of this play, a pioneer in presenting a disposses- sed man in the lead role, work with which Bu?chner would become the precursor of naturalists and expressionists. In the final sections, we discuss the reasons for composing the play Ze?, adaptation in song and verse of Woyzeck. The verse can give the text some musical qualities, which amplify the meanings of the play. Examples taken from Ze? are used to expose such hypotheses.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".