E-RIHS PP D8.2 Report on feasibility studies and integration of new services
Notice bibliographique
Résumé
This deliverable reports about Task 8.2 Feasibility studies, which addresses the viability and manner of eventually incorporating new services, ensuring maximum efficiency for each interested beneficiary community. This is aims at preparing E-RIHS for the delicate implementation phase of E-RIHS, tackling any potential flaws in its services. The feasibility studies concern different potential new services identified. Such potential new services address the common needs and integration of multiple HS communities. In this task small feasibility studies will address the viability and manner of eventually incorporating these services, ensuring maximum efficiency for each interested beneficiary community. This prepares E-RIHS for the delicate implementation of E-RIHS, tackling any potential flaws in its services. All the subtasks listed below concern interoperability and cross-discipline applicability, mostly based on current best practices and involve no additional research. Subtask 8.2.1 – Multilevel analysis: Identification, Digitisation and Reconstruction. Subtask leader: FORTH – Participants: ATOMKI(EK); FORTH(OF_ADC); CENIEH; CNRS(IPANEMA); IPCHS; UCL(NTU) This multidisciplinary Paleoanthropological and Bioarchaeological feasibility study concerned the design of an integrated pipeline involving different analytical techniques (e.g. Isotope, aDNA, Proteomics, Tomography, etc.) and their combination with advanced IT methods (e.g. 3D modelling) and the management of a combined repository. Subtask 8.2.2 – Universal chronology service. Subtask leader: CENIEH – Participants: ATOMKI; CNR(+INFN); CNRS; UCL(+SUERC) The subject of the subtask concerns a feasibility study on the creation of a universal chronology service, comprising all relevant techniques used to date heritage (e.g. C14, luminescence, paleomagnetism). A ‘one door to knock on’ service helping to choose the most appropriate technique, laboratory and sampling. Users include museums, government and heritage-related organizations, art historians, archaeologists. A joint research program will be designed on the technique applicability, protocol homogenisation, training, etc. Subtask 8.2.3 – Workflow in Digital Archaeology and Analytical Methods. Subtask leader: CYI Participants: ATOMKI(HNM); CENIEH; DAI; DP; IAA; KIK-IRPA; UCL(NTU) The feasibility study concerned the analysis and the design of the pipeline from field data documentation to site/artefact analysis, and how this process is recorded, performed and shared in a common knowledge repository while integrating analytical and digital methods. Subtask 8.2.4 – Reference collections. Subtask leader: RCE – Participants: ATOMKI(EK; HNM); CNR; FORTH; IPCHS; LNEC(+HERC); PIN; UCL The subtask investigated how such collections may be mass-produced (RCE) and/or virtualised (PIN), to offer different scientific communities an easier availability of such important research tools and of guidelines for their use, contacting various scientific communities to analyse their needs. Subtask 8.2.5 – Integration of scientific data with general heritage documentation. Subtask leader: PIN Participants: ATOMKI(HNM); CNRS; FORTH; IPCHS; KIK-IRPA; RCE; UCL(+NG; SUERC) The study analysed current best practices and design an integrated system where researchers can discover and use all the information concerning the subject of their study, regardless of its scientific or humanities origin. Subtask 8.2.6 – Advanced materials for restoration. Subtask leader: CNR(CSGI) Participants: CNR; CNRS(+C2RMF); DAI(RRL); FORTH; IPCHS; KIK- IRPA; LNEC(+HERC); UCL(NG) The subtask analysed new solutions for the conservation, and the feasibility study concerns the design of an integrated pipeline involving different analytical tools and innovative materials for the definition of the best conservation procedures to ensure the best practice and maximum efficiency for the beneficiary community. Each subtask work is reported in the deliverable section numbered accordingly. References and appendices, when available, are included at the end of the related section.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».