Study on News Reporting Patterns Based on AR Technology
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
In recent years, AR swept the Chinese market and media academia, setting off a wave of convergence between media industry and AR technology integration. Especially in the aspect of news reports, it has obvious advantages in terms of its Three-dimensional Reporting presentation, Immersion experience, convenient operation and tool neutrality. It has formed a certain impact on the forms, techniques and ideas of news reports, which has an immeasurable development potential. However, the cost of AR news and profit model yet are not resolved, and it has its own limitations. So the media man has new requirements and they must remember. Therefore, this article tries to regard AR news at the center, focuses on the origin and concept of AR news, compares to other media advantages, trends and other aspects of analysis. In the meantime, it also makes a brief statement on the hidden danger of AR news, with a comprehensive and fair perspective to understand and analyze this new era of the new products comprehensively.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| 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 it