Absolute Space or Relational Space, Which Governs Spatiotemporally Extended Effects in Disease Dispersion?
Bibliographic record
Abstract
Prevailing disease models typically focus on in-situ effects, that is, the health risks of a location are affected by the transmission-driving factors of the same location. The ex-situ effects, in contrast, extend health risks from neighboring locations and earlier days to focal locations and current dates. These effects could be critical but have not received much attention. This study investigates the extended effects in absolute space and relational space. We examine whether the effects exist, whether they differ between the two spaces, and whether they vary with the order of neighbors and the number of prior dates in both spaces. Results show that extended effects are generally present. Mild effects are identified in absolute space, while greater effects are observed in relational space. The effects vary slightly with the neighbor order in absolute space, but considerably in relational space where the second-order neighbors exert the most prominent effects. In both spaces, the effects diminish at the third-order and last for up to three days. These findings advocate multiple spatializations that offer an in-depth understanding of disease dispersion in specific and dynamic geographic phenomena at large.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".