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，B案例描写了工行在遭遇互联网金融的逆袭时，如何搭建互联网金融平台，甚至跨界做电子商务：从“银行信息化”到“信息化银行”，究竟是文字游戏还是思维颠覆？工行怎样借鉴互联网金融理念，获得从客户出发的决策思维？工行的电子商务战略，与其他互联网电商相比，有哪些思维上的创新和超越？
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".