Bibliographic record
Abstract
本案例紧接着案例A末尾的决策点介绍道，2010年，诗肯柚木的创始人——林福勤（Pok Chin Lim）与其妻子（Catherine Foo）的第二个孩子Julian Lim得偿所愿，接管了诗肯柚木的日本市场，开始了解诗肯柚木日本的员工，并在拿过交接棒的第一年就尝试改善公司管理架构。在2011年的大地震中，Julian做的员工关怀工作使他在公司树立了威望。到2017年3月，诗肯柚木日本在Julian的领导下取得了巨大的进步。在林氏家族的共同努力下，诗肯柚木在新加坡、台湾、日本和其它国际市场均获得成功。但是，这个家族企业还是面临着一些关键问题，尤其是如何将管理权和家族财富从第一代移交到第二代。
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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".