Bibliographic record
Abstract
This chapter discusses the basic requirements for the design and algorithms of operation of a multi-parametric, synergistic sensory network -Smart Synergistic Security Sensory Network or Net4S -specially adapted for operation at nuclear power plants or other potentially dangerous sites. This network contains sensors of different types and is capable of analyzing the dynamics of environmental processes and predicting the most probable events. The discussion includes analysis of: 1) the technical aspects of operability of the sensors, optical and electrical telecommunication channels, and computers in the presence of ionizing radiation; 2) the influence of environmental parameters on the sensors' accuracy and network operability; and 3) the development of simulators capable of advising safe solutions based on the analysis of the data acquired by the Net4S. Such a real-time operating network should monitor: (1) environmental and atmospheric conditions -chemical, biological, radiological, explosive, and weather hazards; (2) climate/man-induced catastrophes; (3) contamination of water, soil, food chains, and public health care delivery; and (4) large public/industrial/government/military areas. Military personnel, police officers, firefighters, miners, rescue teams, and nuclear power plant personnel may use the mobile terminals (man-operated vehicles or unmanned robots) as separate multi-sensor units for local and remote monitoring. Among different types of sensors, only optical laser sensors can respond immediately and remotely. Such sensors can simultaneously monitor several gases, vapours, and ions with the help of single tunable laser; however, the use of several lasers operating at different, well separated wavelengths, dramatically improves accuracy and reliability, and increases the number of monitored substances. The Net4S, monitoring a number of parameters inside and outside a Nuclear Power Plant (NPP), can serve as the security, safety, and controlling system of the NPP. Besides the technical issues, the chapter also discusses the social aspects of the Nuclear Power Plants' design, construction, and exploitation. Some power consumption-free technologies that significantly improve the reliability of the Nuclear Power Plant are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".