Competitive analysis of current Ocean Web-Mapping Applications
Bibliographic record
Abstract
A competitive analysis study is a usability engineering method administered to critically analyze and compare a set of similar applications according to their relative merits. This paper presents a competitive analysis study of current ocean web-mapping applications that deliver ocean related data to the scientific community. The analysis is part of a User-Centered Design (UCD) approach that was applied to develop the Ocean Web-Mapping Application of the Ocean Mapping Group (OMG) at the University of New Brunswick (UNB), a web mapping application to deliver ocean mapping data to ocean modellers. A total of twenty-four existing applications were critically analyzed and compared across two broad themes in cartography: (1) representation and (2) interaction; adding topics to consider the potential needs of ocean modellers. The results helped to establish trends and gaps and to discover new opportunities for ocean web-mapping development. Using the conclusions drawn from this study, an online survey was prepared to be conducted by ocean modellers and continue the UCD methodology of the Ocean Web-Mapping Application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".