Prevalence and classification of web page defects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to provide an update on previous surveys that have looked at the quality of HTML documents on the worldwide web. Previous surveys have indicated that the quality of HTML documents tends to be quite poor, with most documents containing defects. Design/methodology/approach To determine the extent of this problem, the paper undertook a large‐scale study of HTML document quality among the most popular web sites (approximately 100,000). Findings This paper found that the vast majority (over 95 per cent) of web sites did not adhere to the worldwide web consortium standards for HTML. Research limitations/implications This study represents a single investigation over a short timeframe. Hence, ideally the study needs to be replicated in the future to help generalise the findings. Practical implications Such poor quality may jeopardise the security or usability of a web site, making the site's users vulnerable to malware attacks. This poor level of quality has drastic implications for web usability and security. Originality/value This new survey undertook a more extensive examination of popular web sites than previous surveys.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it