A Review of JavaScript Object Notation in Data Analysis
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
JSON is an extremely popular data format in the 2000s. It is used for transforming the data type. It is not different for reading and writing, and it is simple for machines. As time goes through the age of big data, there appears a group of applications, for example, the two that will be discussed in this essay: NoSQL and NewSQL, for data analysis and big data. The SQL database is always a popular database since the 1980s. In recent years, key-value storage, which always means NoSQL, became more and more popular. Also, the NewSQL database type was developed to solve a similar challenge more efficiently. This essay aims to find the application of these data formats in the real world. According to the research results, JSON could be used as the data format when the data are shifting between the Android application and the Web server.
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 | 0.022 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.011 | 0.024 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.002 | 0.011 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| 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