AB185. SOH25_AB_203. Proposal for a poster introducing pathogens of significance to medical students
Bibliographic record
Abstract
Background: The depiction of pathogens is often challenging. The authors aim to provide a quick, visual reference of the most relevant pathogens for human disease to introduce medical students in preclinical years to medical microbiology and infectious disease. Methods: Authors used a priori knowledge and Volume 2 of Mandell, Douglas, and Bennett’s Principles and Practice of Infectious Diseases (eighth edition) to develop a list of approximately 120 etiologic agents of infectious diseases. Agents were grouped by physiological target system, colour coded by type of pathogen (e.g., virus, fungus, etc.), and given a unique 2-letter abbreviation of the first letters of their genus and species name (except in cases of an existing abbreviation). For 14 organisms, the second letter of their code reflects a different part of their genus/species name due to conflict. An addendum including agents’ incubation periods and clinical presentation of disease will be compiled in consultation with an infectious disease specialist. Results: The proposed poster is intended as an educational resource, designed to resemble the periodic table developed by Mendeleev. The authors intend to provide the most pertinent introductory information for medical students beginning to learn about infectious diseases, including the type of pathogen and the primary system(s) they affect in a single, visually clear reference. Conclusions: Future research will include a pilot study among preclinical medical students at the University of Limerick, allowing for refinement of the materials and eventual assessment of the effectiveness of the poster and addendum as a learning aid for infectious disease material among medical students.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.636 | 0.393 |
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".