Arid Environment and Rock Mineral Content as a Catalyst for Higher Vulnerability to Cancer Morbidity in the Northern State of Sudan
Bibliographic record
Abstract
This study is based on the statement that arid environment and type of mineral content of rocks work together as a catalyst for absorption of higher rates of solar irradiation that will inevitably increase vulnerability to cancer morbidity in the Northern State of Sudan. Sources are published data on climate and geology of Sudan, records of the Ministry of Health and National Population-based Cancer Registry (NCR), and the Internet. Analytical and derivational approaches were applied. The results reveal that the Northern State is a typical arid environment where four solar irradiation regions were distinguished, receiving the highest levels of solar irradiation over the Sudan. The population of the Northern State are susceptible to solar irradiation rates of 6.4 and 6.2 GHI respectively. The majority of rocks belong to silicate minerals groups with dominance of granite rocks with a chemical composition by weight of 72.04% of silica (SiO 2 ). The general average of the solar absorb factor for the three major rock groups was 63.33%. They are inherently acquiring higher ability of absorption of solar irradiation. A general conclusion is that the ecological approach for understanding the etiology of cancer in Sudan is critical.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".