Bibliographic record
Abstract
不确定性已经成为当今企业面临的常态。互联网、移动互联网技术的发展，引发了很多行业的变革，而变革的方向却充满了不确定性，例如互联网金融的挑战，让金融行业未来发展模式充满不确定性。因此，如何预见不确定性、如何解决信息不对称问题，成为置身其中的企业不得不思考的问题。尽管中国工商银行已是全球第一大银行，互联网金融的逆袭，也让它的未来遇到许多挑战。工行董事长姜建清认为：未来不确定性的挑战不在于技术，而在于思想和观念。工行只有用互联网思维替代传统思维，才能不被取代，最终成为互联网生态中的资金、信息和服务中介。本系列共三个案例，A案例描写了工行对未来不确定性的一定程度的预见以及在信息化建设方面的应对措施：拥有国内一流信息技术研发实力的工行为何如此看重这一变化？工行在信息化建设方面采取过哪些措施应对挑战？工行能实现思维模式的改变吗？
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.047 |
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; both teacher heads agree on what is shown here.
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".