Visual Subject Analysis for Dublin Core Research / L'analyse visuelle de sujet aux fins de la recherche Dublin Core
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 primary purpose of this article is to conduct a subject analysis on Dublin Core research, investigate subject topics related to Dublin Core research, and reveal their dynamics over time. Documents related to Dublin Core research were identified in authoritative and comprehensive databases of Web of Science, and subject terms were extracted from the relevant documents. These raw terms were regularized, and the multidimensional scaling (MDS) visualization analysis method was applied to reveal semantic relationships among subject terms. The temporal analysis on the related subject terms added a unique dimension to the study. Three periods (from 1997 to 2001; from 2002 to 2006; and from 2007 to 2011), in addition to the entire period (from 1997 to 2011), were analysed and compared in the visual contexts. Obsolete topics, newly emerging topics, and basic topics on Dublin Core research were identified and analysed in temporal subject analysis. Topic changes in the three periods are shown. The findings of this study reveal the hidden patterns of subject associations, illustrate themes of Dublin Core research and their dynamics over time, and shed light on the understanding of Dublin Core research.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.028 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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