Bibliographic record
Abstract
视源股份成立于2005年，最早将自身定位为TV电视部件供应商，并通过自主创新开发出行业领先的板卡产品，目前已覆盖多种类型电视，全球市占率超过35%。此外，视源还根据时代发展和用户需求，不断增加新业务，开拓新领域。公司先后在会议和教育场景孵化出交互智能平板品牌“希沃（seewo）”和“MAXHUB”，并在两个细分市场都占据行业领先地位。视源高速发展的背后体现出的是管理层追求不断创新的危机意识，同时其供应链管理与组织能力培养也独具特色。2018年视源的营业收入达到169.84亿元，实现业务突破千亿是视源管理层的目标，但要实现这一飞跃还面临不少挑战。
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 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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.022 | 0.019 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.075 | 0.009 |
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".