Design and Construction of a Colourblind-Friendly Surabaya City Angkot Route Map Prototype
Bibliographic record
Abstract
Angkot is the most often found public transportation in Surabaya City. However, there is no angkot routes map, and the officially published route information is textual, thus hard to get the transit information quickly. Meanwhile, people with colour vision impairment have a different perception of colour compared to people with normal vision. It can affect them in making decisions when reading a map. The purpose of this study is to design a colourblind-friendly Surabaya City angkot route map prototype and to conduct a cartographic evaluation of the map by considering the colour vision impairment factor. The map was created using ArcGIS and CorelDRAW then checked by using several software packages to ensure that the colours are colourblind-friendly then tested on people with normal vision and people with colour vision impairment. Fifteen out of 15 respondents with normal vision and 11 out of 11 respondents with colour vision impairment could distinguish the colours of the route. All respondents mentioned that symbols and some texts were too small. It shows that the colours on the map can accommodate both groups, but they have difficulty reading the route map because the size of the symbols and the text is too small.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".