ENHANCING GENOMICS INFORMATION RETRIEVAL THROUGH DIMENSIONAL 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
We propose a novel dimensional analysis approach to employing meta information in order to find the relationships within the unstructured or semi-structured document/passages for improving genomics information retrieval performance. First, we make use of the auxiliary information as three basic dimensions, namely "temporal", "journal", and "author". The reference section is treated as a commensurable quantity of the three basic dimensions. Then, the sample space and subspaces are built up and a set of events are defined to meet the basic requirement of dimensional homogeneity to be commensurable quantities. After that, the classic graph analysis algorithm in the Web environments is applied on each dimension respectively to calculate the importance of each dimension. Finally, we integrate all the dimension networks and re-rank the outputs for evaluation. Our experimental results show the proposed approach is superior and promising.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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