Bibliographic record
Abstract
With the development of the Internet economy today, the business scope of large enterprises has gradually expanded to cross-regional areas, and the development advantages of cross-regional enterprises have gradually become apparent, but at the same time, a series of management and decision-making problems have also arisen. To change the situation of increased costs and reduced efficiency in financial management and decision-making due to the expansion of enterprise scale and the establishment of additional branches, many large Chinese enterprises have begun to try digital finance transformation. Solving the current unclear path of digital finance transformation will help digital finance transformation to be rapidly promoted and implemented in more Chinese enterprises. This study analyzes the features of financial sharing service center (FSSC) in the stage of intelligent and the essence of digital finance transformation. Combined with the development history, organizational framework, operating mechanism and financial data analysis of the management model of Haier Group's FFSC, this research explains the path and future trend of digital finance transformation based on the financial sharing service model, shedding light on offering reference and lessons for the digital finance transformation of enterprises contemporarily.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".