E-RIHS PP 1st Periodic Technical report (from 01/02/2017 to 31/07/2018)
Bibliographic record
Abstract
The report describes the activities carried out in the 1st reporting period of the European project E-RIHS PP (1.02.2017-31.07.2018). The core challenge of E-RIHS PP is to prepare the establishment of the European Research Infrastructure for Heritage Science in the form of an European Research Infrastructure Consortium. E-RIHS ERIC will be a permanent research ecosystem associating people, instruments, competencies and governance to provide innovative research of the highest quality and societal involvement. ERIHS aims to provide a unified scientific approach to the most advanced European instruments, data and services for the analysis, interpretation, preservation, transmission, documentation and management of heritage. E-RIHS associates outstanding research centres and institutes in HS, as well as prestigious research laboratories and conservation centres. Their high reputation arises not only from the international recognition of their scientists and scholars, who combine technical expertise with great historical knowledge of tangible heritage of all types, but also from the variety and quality of the capacities and instrumentations there available. The heart of E-RIHS is then a coordinated group of highly qualified researchers and outstanding instruments and services provided to the European user communities. ERIHS access services will be provided through four integrated platforms: • E-RIHS ARCHLAB: physical access to specialised knowledge and organized scientific information – including technical images, samples and reference materials, analytical data and conservation documentation – in datasets largely unpublished from archives of prestigious European museums, galleries and research institutions. • E-RIHS DIGILAB: online access to scientific data concerning tangible heritage, making them FAIR (Findable-Accessible-Interoperable-Reusable). It includes and enables to access searchable registries of specialized digital resources (datasets, reference collections, thesauri, ontologies, etc.); supports data interoperability through the creation of shared knowledge organization systems and provides tools to process them according to researchers’ needs and research questions. Such data will primarily consist in measurement results and scientific information (texts, images, 3D models and more). • E-RIHS FIXLAB: access to large-scale and medium-scale facilities – particle accelerators and synchrotrons, neutron sources; non-transportable analytical instruments (e.g. micro-CT) – offering a unique expertise to users in the heritage field for sophisticated scientific investigations on cultural and natural heritage objects, both samples and whole items, revealing their microstructure, chemical composition and age, giving essential and invaluable insights into historical technologies, materials, alteration and degradation phenomena or authenticity. • E-RIHS MOLAB: access to an impressive array of advanced mobile analytical instrumentation for non-invasive measurements on precious, fragile or immovable objects, archaeological sites and historical monuments. The MObile LABoratory allows its users to implement complex multitechnique diagnostic projects, permitting the most effective in situ investigations.
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.
How this classification was reachedexpand
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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.065 | 0.073 |
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; both teacher heads agree on what is shown here.
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".