2022-2023 IgNITE Medical Case Competition: CardioRespiratory Medicine
Bibliographic record
Abstract
The IgNITE Medical Case Competition is an annual research case competition organized by students across North America. Our mission is to provide high school and university students the opportunity to gain valuable research experience while networking with industry professionals. Each year, students in teams of 1-4 are paired with an experienced mentor to develop and present a novel research proposal within a specified theme of the competition. Students are taught the fundamental scientific principles underlying three lab techniques which can be applied in their proposal for the competition or used in their future research career. This year's theme was CardioRespiratory Medicine, and competitors learned about RNA Sequencing, Model Organisms, and In vivo imaging systems. Furthermore, the IgNITE community grew internationally this year with over 550 high school and university students participating in the competition. Presented in this booklet are the Top 40 teams' abstracts and we invite you to visit our website (www.ignitecompetition.org) to watch their associated elevator pitch videos. We hope you enjoy reading through some of this year's top proposals and encourage you to join our ever-growing community.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".