E-RIHS PP D8.2 Report on feasibility studies and integration of new services
Bibliographic record
Abstract
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.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".