Bibliographic record
Abstract
ABSTRACT Objectives : to determine the prevalence of pain in homeless people from downtown Sao Paulo, characterize it, unveiling its implications for general activities present in the Brief Pain Inventory. Method : descriptive, exploratory, cross-sectional study with a quantitative approach. The sample is composed of registered homeless by a Street Clinic team. The instruments used in data collection will be the form of recruitment of inclusion/exclusion criteria, form of socio-demographic data, Brief Pain Inventory, McGill Pain Questionnaire and Wong-Baker Face Scale. Expected results : it is visible the homeless pain to offer subsidies for a competent evaluation of that pain, better control and treatment by health teams. Descriptors : Pain; Homeless; Nursing; Culturally Competent Health Care; Access to Health Services. RESUMO Objetivos : conhecer a prevalencia da dor nos moradores de rua do centro de Sao Paulo, caracteriza-la, e desvelar suas implicacoes nas atividades gerais que compoem o Inventario Breve de Dor. Metodo : estudo descritivo-exploratorio, transversal, com abordagem quantitativa. A amostra sera composta por moradores de rua cadastrados por uma equipe de Consultorio na Rua. Os instrumentos utilizados na coleta de dados serao o formulario de recrutamento de criterios de inclusao/exclusao, formulario dos dados sociodemograficos, Inventario Breve de Dor, Questionario de Dor McGill e Escala de Face Wong-Baker. Resultados esperados : tornar visivel a dor do morador de rua para oferecer subsidios para uma avaliacao competente desta, melhor controle e tratamento pelas equipes de saude. Descritores : Dor; Morador de Rua; Enfermagem; Assistencia a Saude Culturalmente Competente; Acesso aos Servicos de Saude. RESUMEN Objetivos : conocer la prevalencia del dolor en las personas sin hogar del centro de Sao Paulo, caracterizarlas, desvelar sus implicaciones en las actividades generales que componen el Inventario Breve de Dolor. Metodo : estudio descriptivo-exploratorio, transversal, con enfoque cuantitativo. La muestra sera compuesta por personas que viven en la calle registrados por un equipo de Consultorio en la Calle. Los instrumentos utilizados en la recoleccion de datos seran el formulario de reclutamiento de criterios de inclusion/exclusion, formulario de los datos socio-demograficos, Inventario Breve de Dolor, Cuestionario de Dolor McGill y Escala de Face Wong-Baker. Resultados esperados : tornar visible el dolor de la persona que vive en la calle para ofrecer subsidios para una evaluacion competente de ese dolor, mejor control y tratamiento por los equipos de salud. Palabras clave : Dolor; Personas sin Hogar; Enfermeria; Asistencia a la Salud Culturalmente Competente; Acceso a los Servicios de Salud. Normal 0 21 false false false PT-BR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:Tabela normal; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:Calibri,sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:Times New Roman; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Times New Roman; mso-bidi-theme-font:minor-bidi;}
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".