Additional file 1 of Rapid review of COVID-19 epidemic estimation studies for Iran
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 1: Appendix Text 1. Search syntax used in PubMed. Appendix Text 2. Details of studies’ scenario. Appendix Table 1. Predictions of cumulative cases for the end of months one to six after the official epidemic start date (2020-02-19) and the latest date available in 2020. Appendix Table 2. Predictions of daily deaths at end of months one to six after the official epidemic start date (2020-02-19) and the latest date available in 2020. Appendix Table 3. Predictions of daily cases for the end of months one to six after the official epidemic start date (2020-02-19) and the latest date available in 2020. Appendix Table 4. Predictions of epidemic peak dates and values of outcomes. Appendix Table 5. Predictions of epidemic control dates and values of outcomes. Appendix Figure 1. PRISMA 2009 study flow diagram. Appendix Figure 2. Officially reported cumulative confirmed cases, deaths, and recovered cases of COVID-19 in Iran. Appendix Figure 3. Reported daily confirmed cases, deaths, and recovered cases of COVID-19 in Iran. Appendix Figure 4. Reported and median-scenario estimated daily prevalent cases of COVID-19 in Iran, including predictions by Saberi. Appendix Figure 5. Reported and median-scenario estimated daily prevalent case of COVID-19 in Iran, without predictions by Saberi. Appendix Figure 6. Reported and worst-scenario estimated cumulative deaths of COVID-19 in Iran, including predictions by Mashayekhi. Appendix Figure 7. Reported and worst-scenario estimated cumulative deaths of COVID-19 in Iran, without predictions by Mashayekhi. Appendix Figure 8. Reported and current (median) scenario estimated cumulative deaths of COVID-19 in Iran, International studies.
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 | 0.018 |
| 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) | 0.991 | 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