Relatório de estágio curricular supervisionado em medicina veterinária – área: clínica médica de pequenos animais
Bibliographic record
Abstract
O Estagio Curricular Supervisionado em Medicina Veterinaria (ECSMV) e constituinte obrigatorio para graduacao em Medicina Veterinaria, sendo o foco deste a Clinica Medica de Pequenos Animais. No presente relatorio estao descritas as atividades realizadas no periodo de quinze de janeiro a seis de abril de 2018 totalizando 456 horas, acompanhando o Medico Veterinario Rodrigo Giordani Ritt atuante na cidade de Santa Rosa-RS sob orientacao institucional da Profa. Dra. Mauren Picada Emanuelli. As atividades realizadas foram relacionadas a participacao e acompanhamento de 122 atendimentos, sendo 108 caninos e 14 felinos, com as enfermidades do sistema tegumentar possuindo maior incidencia. Foram executados e/ou acompanhados 502 procedimentos, entre eles coletas de sangue, vacinacao e vermifugacao. O ECSMV serviu como forma de colocar em pratica o conhecimento adquirido ao decorrer da vida academica, alem de proporcionar outros aprendizados necessarios e imprescindiveis a insercao no mercado de trabalho. A seguir serao relatados a rotina clinica vivenciada, alem de dois casos clinicos, um de displasia coxofemoral em um Labrador Retriver e um caso clinico de uma cadela Sem Raca Definida com cisto folicular ovariano.
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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 | 0.003 | 0.012 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".