Map-based interfaces for common operational picture
Bibliographic record
Abstract
Common operationalpicture (COP) map-based interfacesdisplay operational information to support integrationofemergency responders. Such interfacesintegrate different subsystems and present the resulting information into an overview for enabling situation awareness. Literature shows that they are often developed from non-user-centric perspectives and are defined in technological terms that arenot adequately capturing the users’ needs. Therefore,theaim of this particular work in progressis to get insight into the features and the role of COP map-based interfaces currently being used in Norway to (1) examine theircontent, functionality, and design;and(2) to understand how such displays are incorporated into the servicecontext.This studystructuresthe knowledge on map displays that constitute part of the COP services.Using workshopand interviews with the developers and usersof existing COP map services, we identify requirements for a common operational symbology and common operational functionality to improvesuch map services andmake them interoperable.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.024 |
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".