iNeuro: Technology and Business Model Innovation of EEG Platform
Bibliographic record
Abstract
妞诺科技的创始团队都是脑电领域的研究学者，受科研项目启发开始探索脑电技术商业化的可能性。妞诺最初从脑电图机切入，通过自研硬件的升级取得了一系列医疗器械认证，并逐渐与一些医院建立了合作关系。自主研发的硬件帮助妞诺获取到高质量的脑电数据，再结合团队本身的数据挖掘和分析能力，公司从单一的脑电解决方案供应商逐渐转型为多模态脑科学数据平台。 妞诺科技的创智指的是公司基于医疗器械研发和数据挖掘分析所做的技术创新，创制指的是公司通过细分市场、业务范围和价值主张的调整所做的商业模式创新。 妞诺是如何一步步打造核心竞争力并发展出如今的商业模式的、未来又应该如何发展呢？此外，虽然大数据服务是当下的一个热点，但可持续的盈利点尚不清晰，且妞诺团队的销售经验相对薄弱。目前公司已完成了三轮融资，投资人对于项目回报也有自己的预期，公司下一步走向何方？是继续寻觅投资人、冲刺科创板还是投靠大公司？这些都是创始团队需要考虑的问题。
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".