A 4D Decentralized Spatiotemporal Mirror World: Building a Conceptual Model of Cultural Heritage Resilience Through the Integration of Co-creation, Gamification, Tokenization, and the Metaverse
Bibliographic record
Abstract
Heritage assets, such as historic buildings and archaeological sites, are prone to the cycle of changes, threatened by man-made and natural hazards.As such, resilient policies, which minimize the period of recovery/restoration, after the loss of heritage assets, are often based on the digitization of cultural goods. However, due to inadequate funding, lack of specialized personnel, and time constraints, the likelihood of such recovery measures has been limited. Supported by the case study research model, this research aims to minimize the effects of such limitations by constructing a conceptual model of a 4D decentralized spatiotemporal Mirror World. The platform allows for global collaboration in digitizing the past, present, and future of our urban environment through personally own mass media devices. By incorporating NFT-based mechanisms, such as ownership and play-to-earn, contributors will remain as the sole creator of the submitted photo/data while potentially generating forms of profit through gamified contributions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".