Author manuscript, published in "11th International Symposium for GIS and Computer Cartography for Coastal Zone Management (CoastGIS 2013), Victoria: Canada (2013)" A dynamic GIS as an efficient tool for ICZM (Bay of Brest, Western France)?
Bibliographic record
Abstract
This contribution deals with the role of geographical information in participatory research concerning coastal zones and its potential to bridge the gap between research and coastal zone management. The study aims at modeling the interactions between human activities in a maritime basin. A dynamic GIS is used as a tool to facilitate the exchange of points of view and to share knowledge. Geographic information technologies are used at several levels: data collection, GIS analysis, mapping, and simulations. The results show that the GIS-based capture data is well managed by the stakeholders who are interested in contributing to the process of gathering scientific data. The results of a participatory workshop with stakeholders show that the dynamic component of the data adds a real value for management. The possibility to use such a dynamic GIS to discuss and simulate management scenarios is tested, but it needs to be built up gradually.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.484 | 0.163 |
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".