Geosemantic Proximity to Improve Geospatial Information Discovery in a Wireless Environment
Bibliographic record
Abstract
Davantage de sources de donnees geospatiales, elaborees pour des besoins particuliers selon differentes ontologies, peuvent maintenant etre accedees a l'aide d'ordinateurs de poche ou d'assistants numeriques personnels (PDA) branches sur Internet a l'aide de connexions sans fil et de fureteurs Web sur des telephones cellulaires qui utilisent le protocole WAP. Dans cet article, nous proposons une solution pour accroitre l'efficience des engins de recherche de donnees geospatiales. Plus specifiquement, nous elaborons un cadre conceptuel d'interoperabilite des donnees geospatiales et la notion de proximite geosemantique pour interagir avec des bases de donnees geospatiales qui peuvent etre utilisees dans un environnement sans fil. Des exemples illustrent la pertinence de cette notion qui appuie la recherche efficiente de donnees geospatiales sur le Web, specialement dans un environnement sans fil. Finalement, nous abordons succinctement des resultats obtenus a l'aide de notre prototype.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".