Investigating Web3D topics on StackOverflow: a preliminary study of WebGL and Three.js
Bibliographic record
Abstract
Web3D developers often have to decide on which technologies are best for their projects. We explore that question through the perspective of community attention and support on Stack Overflow (SO). We focused on i) WebGL, a key low-level JavaScript (JS) API used to render 3D graphics in browsers without plugins, and ii) Three.js, a higher level JS library that reuses WebGL and is reputed easier and more intuitive. We considered questions from SO tagged with WebGL or Three.js and extracted all tags used on these questions. Using these, we were able to compare the relative attention (considering the number of questions and views) and support (considering satisfactory answers and how long they take) received by concerns and technologies associated to WebGL and Three.js. Our results suggest that Three.js gets significantly more community attention but less community support than WebGL on SO.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".