Technogenic dangerous objects environmental impacts assessment: scientific and theoretical basis, practical implementation
Bibliographic record
Abstract
Based on comparative analysis of the procedures of environmental impacts assessment (EIA) established in the leading countries of the world - the USA, Canada, Great Britain, Federal Republic of Germany, Japan, Latin America and the Caribbean, Hong Kong, Netherlands, Denmark, Sweden, Finland, Norway, Iceland, Israel, South African Republic, Australia - the basic stages of the EIA implementation in Ukraine were grounded: screening, scoping, alternative, public participation, assessment of environmental situation. These stages are to be carried out in the beginning of any technogenic object planning and to accompany the process of its construction and exploitation. The new methods of determination of present environmental situation of territory and object by the means of geoinformational technogeochemical modeling and prognosis of the environmental situation are offered. The structure of databases of environmental information is grounded for ten components of ecosystem that allowed improvement of the methods of the components mapping on the grounds of new GIS-technologies. For the first time complete geoinformational system of environmental safety is developed for ой and gas, energy, recreational and tourist sectors based on different investment projects in Ukraine.\nThe EIA procedure should precede to any planned activity - this theoretical conclusion of the candidate was implemented in oil and gas fields, while planning ash-slag dumps of the Burshtyn heat power plant, power lines construction, small hydropower plants and construction of the new skiing resorts "Bukovel" and "Bystrytsya" in the Carpathians.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".