Development and integration of digital technologies addressed to raise awareness and access to European underwater cultural heritage. An overview of the H2020 i-MARECULTURE project
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
The Underwater Cultural Heritage (UCH) represents a vast historical and scientific resource that, often, is not accessible to the general public due the environment and depth where it is located. Digital technologies (Virtual Museums, Virtual Guides and Virtual Reconstruction of Cultural Heritage) provide a unique opportunity for digital accessibility to both scholars and general public, interested in having a better grasp of underwater sites and maritime archaeology. This paper presents the architecture and the first results of the Horizon 2020 i-MARECULTURE (Advanced VR, iMmersive Serious Games and Augmented REality as Tools to Raise Awareness and Access to European Underwater CULTURal heritage) project that aims to develop and integrate digital technologies for supporting the wide public in acquiring knowledge about UCH. A Virtual Reality (VR) system will be developed to allow users to visit the underwater sites through the use of Head Mounted Displays (HMDs) or digital holographic screens. Two serious games will be implemented for supporting the understanding of the ancient Mediterranean seafaring and the underwater archaeological excavations. An Augmented Reality (AR) system based on an underwater tablet will be developed to serve as virtual guide for divers that visit the underwater archaeological sites.
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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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