Research on XBRL Domain Ontology Construction
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
XBRL (eXtensible Business Reporting Language) as an application of XML (eXtensible Markup Language) technology in the field of business reporting, uses information technology to add tags for the financial reporting metadata, to achieve unstructured data processing effectively. At first, this paper analyzes the XBRL technology framework, finds out the concepts and relationships between them, and accordingly designs the XBRL domain ontology model, then based on the model we have proposed, we choose OWL DL ontology description language and Protégé3.4, take balance sheet as an example, and apply the XBRL ontology model to balance sheet to construct the taxonomy and instance, and thereby achieve the implementation of XBRL domain ontology construction. XBRL needs the integration of the accounting, engineering, computer, management and other disciplines, and the future research should be committed to solve the lack of semantic and reasoning mechanism to implement the further promotion and application of XBRL financial reporting.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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