The Landscape of Digital Technology to Enhance the Digital Researcher
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
The objectives of this research were to synthesize the competencies of the digital researcher, carry out an empirical investigation of the digital researcher landscape, and evaluate the results of a synthesis of digital researcher competency. To conduct the research, the researchers carried out a review of the literature related to researcher competency, digital competency, digital researcher competency and digital technology for researchers. Then, a focus group discussed the conclusion of the digital technology landscape used to enhance the digital researcher. The results showed that digital researchers’ competency had six features: 1) Personalize and Security Competency, 2) Literature Review and Reference Management Competency, 3) Communication and Collaboration Management Competency, 4) Analyzing and Reporting Competency, 5) Proofreading and Plagiarism Checking Competency, and 6) Publication Competency.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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