Additional file 4 of Long-term humoral and cellular immunity after primary SARS-CoV-2 infection: a 20-month longitudinal study
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
Additional file 4: Supplementary Figure 4. Impact of SARS-CoV-2 vaccination on humoral and cellular immunity for S-small and non-S immunity. Analysis of a subset of 65 patients who received their first 2 vaccinations between two subsequent visits (Prior: A visit where the participant had not been vaccinated, Post: The subsequent visit, where the participant had received 2 vaccinations). (A) Percentage of SARS-CoV-2 spike (S)-specific CD4+ and CD8+ T cells analysed by AIM after stimulation with the S-small pool. (B) IFNγ production by SARS-CoV-2 S-specific cells (S-small pool). (C) SARS-CoV-2 nucleocapsid-specific IgG levels (D) Percentage of SARS-CoV-2 S-specific CD4+ and CD8+ memory T cells analysed by ICS after stimulation with the non-S peptide pool. (E) Percentage of SARS-CoV-2 non-S-specific CD4+ and CD8+ T cells analysed by AIM. (F) IFNγ production by SARS-CoV-2 non-S-specific cells. Horizontal line shows median Statistical comparisons were performed using Wilcoxon unpaired signed-ranks test adjusted using Bonferroni. *P ≤ 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.
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) | 0.931 | 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