Vertical Colour Maps – A Data-Independent Alternative to Floor-Plan Maps
Bibliographic record
Abstract
Location sharing in indoor environments is limited by the sparse availability of indoor positioning and lack of geographical building data. Recently, several solutions have begun to implement digital maps for use in indoor space. The map design is often a variant of floor-plan maps. Whereas massive databases and GIS exist for outdoor use, the majority of indoor environments are not yet available in a consistent digital format. This dearth of indoor maps is problematic, as navigating multistorey buildings is known to create greater difficulty in maintaining spatial orientation and developing accurate cognitive maps. The development of standardized, more intuitive indoor maps can address this vexing problem. The authors therefore present an alternative solution to current indoor map design that explores the possibility of using colour to represent the vertical dimension on the map. Importantly, this solution is independent of existing geographical building data. The new design is hypothesized to do a better job than existing solutions of facilitating the integration of indoor spaces. Findings from a human experiment with 251 participants demonstrate that the vertical colour map is a valid alternative to the regular floor-plan map.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".