Hydroweb: an Open Source educational WebGIS platform for the understanding of spatio-temporal variations of meteorological parameters at the watershed scale
Bibliographic record
Abstract
GIS is an interdisciplinary technology able to support high-level thinking and spatial reasoning. It allows students to visualize complex real world problems, and supports multiple modes of learning. But GIS remain unused at the primary school level. Indeed, there is a gap between a declared interest in GIS technology and their effective slow rate of implementation in classrooms. The complexities of desktop GIS are possible brakes on their adoption in schools. They can be cut by using web-based GIS solutions. Indeed, internetbased mapping provides an invaluable way for establishing GIS technology in the primary and secondary education (“K-12 education community” in USA and Canada), while avoiding the main barriers associated with desktop GIS. Such tools can support standard methods of teaching and learning while providing basic analysis tools for studying and exploring geographic or other scientific data in the classroom. This kind of platform is ideal for many teachers and 12-14 years old children that are not able to spend the time and energy required to run desktop GIS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.014 |
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".