Virtual Instrument Reading Consistency Fact Verification Dataset
- Records
- 5540
- Size
- 0.4GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
This JSON dataset records virtual laboratory instrument calibration status, settings, raw readings, export details, and unit conversion results, alongside significant-digit checks and reading consistency verdicts. By linking instrument status, range, values, units, and exported records, it supports the detection of conflicts and inconsistencies in virtual experiment data. Typical uses include fact-verification model training, experiment result review, and structured numerical validation.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| export_record | object | Source records of exported values, units, displayed text, and export timestamps from the virtual instrument. |
| validation_label | string | Overall fact-verification label for model training and evaluation. |
| calibration_record | object | Source records of the virtual instrument's calibration status, reference values, and calibration validity period. |
| raw_reading_record | object | Raw readings obtained directly from the virtual instrument interface or measurement API, together with instrument status. |
| instrument_settings | object | Pre-experiment target values, units, resolution, range, and other parameters configured for the virtual instrument. |
| normalization_result | object | Normalized values and conversion parameters calculated from the raw reading unit and target unit. |
| significant_digits_check | object | Validation results from comparing the original display text, configured resolution, and exported text. |
| fact_validation_statement | string | A Chinese-language factual statement about consistency, generated from all source records and derived verification results. |
| reading_consistency_verification | object | A fine-grained consistency verdict based on instrument status, range, units, values, significant digits, and export records. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What does the dataset contain?
- It includes instrument calibration records, settings, raw readings, export records, unit conversion results, significant-digit checks, reading consistency verdicts, and overall validation labels. These fields support analysis linking source information to verification outcomes.
- Which tasks is the dataset suited for?
- It is suited for fact verification, numerical and unit consistency checks, significant-digit validation, and experiment result review based on structured records. Training methods can be adapted to the model input format and target labels.
- Are sample counts or quality metrics specified?
- The available description does not specify sample counts, instrument coverage, or quantitative quality metrics. Before selecting the dataset, review the product listing for its actual scale, field examples, and data quality information.
- How can I obtain the data, and what are the license terms?
- Check the product page for available download or delivery options and the applicable license and usage restrictions. Review the specific terms before commercial deployment, redistribution, or other specialized use.
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Cite this Work
@dataset{Mobiusi2026,
title={Virtual Instrument Reading Consistency Fact Verification Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/88056408cf8235a5866ae9e42bfce2ab?dataset_scene_cate_type=2},
urldate={2026-10-27},
keywords={virtual instrument dataset,reading consistency verification,fact verification data,virtual experiment data,instrument calibration records,unit conversion validation,significant digit checking,experiment result review},
version={1.0}
}Using this in research? Please cite us.