Bibliographic record
Abstract
Há sempre em nossas vidas um alguém para nos inquietar, impacientar, amolecerou fecundar, e, para nossa grande alegria, nunca nos falta aquele sujeito que nossuspende e faz nossa existência evaporar como fumaça que cura as dores das nossasidéias enferrujadas. Tenho no meu amigo Zé um desses sujeitos: seu codinome curtodisfarça a extensão de seu caráter e da candura com que entretece um diálogo. Seunome completo é José Gatti1 , um amigo educa-a-dor. E foi exatamente por eu terficado em “suspenso” durante uma fala sua em um congresso que eu resolvi há poucoprocurá-lo para detalhar as lembranças que recolhi daquela comunicação. Ressalvas:[1] tive de ser parcimonioso, dado o espaço da coluna, já que o Zé quando conversa fazpor alargar minhas fronteiras ad infinitum; [2] este texto é um recorte das intençõesque o texto de sua fala continha; e [3] ao ler este meu texto veja o Zé briosamentefalando e eu ensaiando uma notação oxalá inspirada e quiçá pouco adulterada de seuconhecimento panorâmico.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.060 | 0.015 |
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".