Investigação das propriedades psicométricas da Escala de Alexitimia de Toronto em indivíduos com e sem Transtorno do Comportamento Sexual Compulsivo
Bibliographic record
Abstract
Para sempre cunhadas.Obrigada por deixar eu fazer parte de sua família.Agradecimentos também para minha prima Suzana da Silva Takada, esforçada, franca e firme em seus propósitos, esteve comigo em momentos difíceis.E, por fim, para a prima Roberta Farias, um encanto de pessoa, amável, vibrante e sincera.Grata por me acolher e compartilhar seu espaço comigo e se tornar minha amiga.Agradeço os participantes da pesquisa e os pacientes que me ensinaram tanto sobre o tema e sobre a vida, pois confiaram na relação terapêutica para compartilharem suas dores mais íntimas.Agradeço a CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) pela concessão da bolsa do mestrado. "Quanto sexo é demais? Quanto é suficiente? E quem decide?Groneman (2000, p. 151).
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".