Bibliographic record
Abstract
本案例立足于整个工业AI赛道崛起的背景下，聚焦科技型创业企业，描述了上海快仓智能科技有限公司（以下简称“快仓”）在创始人杨威的带领下，凭借着争做“中国Kiva”的初心，从移动机器人尚未获得投资人关注时进入赛道，在初期缺乏知识体系储备、缺乏人力、物力、财力的情况下，如何一步步进行策略转型、最终发展成为国内移动机器人的领军企业的全过程。随着全球人力成本持续上涨，越来越多的工厂、仓库开始使用机器人搬运、拣选、分拣，快仓作为国内首批进入移动机器人赛道的创业企业，从第一代AGV（Automated Guided Vehicle，自动导引车）到第三代AMR（Autonomous Mobile Robot，自主移动机器人）不断进行技术与产品创新。然而，面对愈发拥挤的赛道，快仓未来如何去满足不同行业和规模的客户需求，保持行业领先与高速增长，是值得探讨的重要问题。
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.105 |
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".