Bibliographic record
Abstract
Abstract Research into the immunoregulation of type I diabetes (T1D), (an autoimmune disease that results in the destruction of insulin producing B cells in the pancreas), is the focus of this curriculum unit. The unit entitled “Researching Type I Diabetes” has been developed for high school students. This unit is designed to be used in classes such as health science, biology, or honors biology. The unit begins with a lesson on the immunoregulation of T1D via the use of a roundhouse diagram activity. Students then learn about the NOD mouse as a model in T1D research, and the legal and ethical aspects of using animals in medical research, to complete a persuasive writing activity involving bioethics. The third lesson requires students to follow a mouse dissection protocol. Following this protocol, students dissect the major organs of the mouse’s immune system (thymus and spleen) to isolate peripheral lymphatic nodes. Then the students observe a teacher demonstration of flow cytometry and cell sorting and why they are essential tools in the understanding of the immunoregulation of the disease. The culminating component of this unit is a “Web Quest,” in which students role-play the various roles involved in clinical and experimental research of T1D. The roles include: scientists, T1D patients, graduate students, physicians, and institutional review board members. Consequently, the students produce and present the results of their “Web Quest” to their classmates in a PowerPoint format.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.268 | 0.167 |
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".