METIS: Dependable Cooperative Systems for Public Safety:
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
Much, if not most, information needed to assess a crisis situation originates these days from cooperative sources such as the Internet and social networks. Public safety authorities face the challenge to compile this information of uncertain origin and quality in their situation understanding and response planning. Time matters: the integration of uncertain information needs to be done in a fast, goal-driven and ad-hoc manner.Such situation understanding requires system support in the form of a dependable and cooperative system-of-systems: able to adapt semi-automatically to new situations and to improve the value of the information using built-in reasoning and awareness techniques. The METIS project researches such system support for public safety as a collaborative project of Dutch universities, knowledge institutes, and industry, using the maritime domain as case study. The METIS goal stretches the scope of system engineering, as the main requirements of ad-hoc adaptation and dependability contradict each other.In this paper, we describe the METIS information architecture and highlight our four major research lines: (i) System architectures beneficial for dependability and adaptability; (ii) Application and system dependability ensured by embedded awareness; (iii) Ad-hoc system adaptability and goal-driven system reconfiguration; (iv) Integration and semantic alignment of various (natural language) information sources
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it