Bibliographic record
Abstract
<p>The purpose of this research is to examine the best practices to adopt modern API technologies, web servers, and frameworks to create tools that run on most design/creative industry software. This system is mainly for time, task, and project management on the remotely executed projects, which individual visual designers and teams can use. A prototype was created to support this research and demonstrate and examine the further possibilities of this system. The prototype is in the form of an extension for Adobe XD. Moreover, it analyzes the time and activity of the end-users.</p> <p>The prototype was created to study the effectiveness of a non-linear time/task management ecosystem for remote workers, primarily users in the creative community who work on visual development software. It can also be utilized to study and validate the efficacy of using an interconnected supervision agent for teams. Consequently, it provided a platform to determine how a team can manage the time and tasks without being sidetracked using a third-party service and focus on the work at hand by staying within the same workspace where the project is being executed.</p> <p>Ultimately, a PWA (progressive web application) was created to share usage analytics and tasks publicly on the web. Additionally, an API was designed and built to store the data and make it available for further production. The API, built on Node.js, stores data in a NoSQL database and makes it available to other applications and platforms.</p> <p>The relationship between these parts illustrated a productive way for experts to stay connected with the project managers who are not necessarily skilled in using the design tool. In addition, the difference in how the user interface was designed for each section provided means to examine the benefit of providing multiple user-fronts while keeping the data consistent among the designers/developers and the managers/clients.</p>
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.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| 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".