Microbiome bacterial influencers of host immunity and response to immunotherapy
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 gut microbiota influences anti-tumor immunity and can induce or inhibit response to immune checkpoint inhibitors (ICIs). Therefore, microbiome features are being studied as predictive/prognostic biomarkers of patient response to ICIs, and microbiome-based interventions are attractive adjuvant treatments in combination with ICIs. Specific gut-resident bacteria can influence the effectiveness of immunotherapy; however, the mechanism of action on how these bacteria affect anti-tumor immunity and response to ICIs is not fully understood. Nevertheless, early bacterial-based therapeutic strategies have demonstrated that targeting the gut microbiome through various methods can enhance the effectiveness of ICIs, resulting in improved clinical responses in patients with a diverse range of cancers. Therefore, understanding the microbiota-driven mechanisms of response to immunotherapy can augment the success of these interventions, particularly in patients with treatment-refractory cancers.
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 | 0.001 | 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