Bibliographic record
Abstract
This paper deals with the management of large rivers from systems theory and human ecology perspective. Natural systems, hierarchy and equilibrium have been widely discussed earlier on, but their relations with human-made structures and modifications on large rivers is a less covered area. One of the key statements in this field is Type One error, the inherent conflict between human-made structures and natural processes. The renewable energy concept, when applied to water resources, has some traps and misleading implications. In fact, renewable sources – including water – can also be depleted if their rate of replenishment is exceeded. Economy-driven river regulations and land use practices triggered a series of events where the system feedback of the river was not taken into account. As a result, the need for yet further manipulations and interference kept on returning, entailing even more and more costs, increased risks and destabilising natural systems. Sustainable river management takes a fresh look at the problem, with historical examples from places like the Carpathian Basin, Mesopotamia or citing recent practices from Thailand.
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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 | 0.156 | 0.509 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".