Towards a Conceptual Framework for WikiGIS
Bibliographic record
Abstract
As an emerging complex concept, GeoDesign requires an innovative theoretical basis, tools, supports and practices. For this reason, we propose a new concept, “WikiGIS”, designed to answer some dimensions of the GeoDesign process. WikiGIS focuses on the needs of GeoDesign, but we leave the door open for future improvement when tested in other areas that may have additional needs. WikiGIS is built on Web 2.0 technologies—and primarily on wiki—to manage the tracking of participants’ editing (i.e., managing the contributions history). It also offers GIS functions for geoprocessing and a design-based approach for sketching proposals. One of the main strengths of WikiGIS is its ability to manage the traceability of contributions with an easy and dynamical access, data quality and deltification. The core of this paper consists of presenting a conceptual framework for WikiGIS using UML diagrams. A user interface is presented later to show how our WikiGIS proposal works. This interface is simply a means to illustrate the concepts underlying WikiGIS.
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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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.020 | 0.027 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".