Bibliographic record
Abstract
Resumo: A nossa condição de seres humanos frente à realidade é, desde a Grécia, uma questão pulsante. Procuramos captar e compreender a multiplicidade das coisas que se nos apresentam e o instrumento que temos para isso é sempre o λόγος; em todos seus inúmeros sentidos. Nesse caso, perguntamo-nos, desde sempre: seria esse λόγος; capaz de exprimir todas as realidades que existem para o ser? Tomando como ponto de partida essa pergunta, procuramos em nosso trabalho analisar alguns aspectos da poesia do último dos trágicos gregos, Eurípides, onde observamos as possibilidades da linguagem frente às realidades possivelmente inexprimíveis.Palavras-chave: Eurípides; tragédia grega; λόγος.Abstract: Our status as human beings confronted with reality has been, since classical Greece, a palpitating question. We try to capture and comprehend the multiplicity of elements that are presented to us, and the tool we have to do is always the λόγος, in all the realities that there are for a given being? Departing from this question, in our work, we try to analyze some aspects in the poetry of the last of tragic Greeks, Euripidis, through wich we observed the possibilities offered by language confronted with realities that are possibly inexpressible.Keywords: Euripidis; Greek tragedy; λόγος.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".