Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The intestinal microbiota and gut immune system must constantly communicate to maintain a balance between tolerance and activation: on one hand, our immune system should protect us from pathogenic microbes and on the other hand, most of the millions of microbes in and on our body are innocuous symbionts and some can even be beneficial. Since there is such a close interaction between the immune system and the intestinal microbiota, it is not surprising that some lymphomas such as mucosal-associated lymphoid tissue (MALT) lymphoma have been shown to be caused by the presence of certain bacteria. Animal models played an important role in establishing causation and mechanism of bacteria-induced MALT lymphoma. In this review we discuss different ways that animal models have been applied to establish a link between the gut microbiota and lymphoma and how animal models have helped to elucidate mechanisms of microbiota-induced lymphoma. While there are not a plethora of studies demonstrating a connection between microbiota and lymphoma development, we believe that animal models are a system which can be exploited in the future to enhance our understanding of causation and improve prognosis and treatment of lymphoma.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it