Bibliographic record
Abstract
China should break away with big country and bi companies complex. Sino-Belgian trade mode, namely government—NGOs—financial organizations unite into one to support bilateral cooperation of small corporations, trade expansion accompanying with technological innovations, can offer beneficiary experiences to both further Sino-EU trade and China’s economical transformation. Keywords: Sino-Belgian trade mode, high-tech cooperation of Sino-Belgian small companies, technological innovation Resume: La Chine doit changer l’idee qui s’attache surtout au grand pays et a la grande entreprise, developper et elargir davantage la cooperation et les echanges avec les petits pays et entreprises europeens qui devraient jouer le role principal dans la cooperation regionale sino-europeenne. Le mode de developpement economique et commercial sino-belge – etablir un contact direct entre le gouvernement, les O.N.G et les institutions financieres, soutenir la cooperation de haute technologie des petites et moyennes entreprises, promouvoir le developpement du commerce bilateral par l’innovation technologique – contient beaucoup de revelations sur le developpement economique et commercial de la Chine avec les autres petits et moyens pays europeens. Mots-cles: modele de developpement economique et commercial sino-belge, la cooperation de haute technologie des petites et moyennes entreprises, innovation technologique 摘要:中國要打破大國及大公司迷信，大力發展和擴大與眾多歐洲小國和中小企業經貿合作和往來，小國集體主導中歐區域合作。中比經貿發展模式——以政府— NGO—金融機構一體化建立直接溝通管道，扶持雙方中小企業高科技經貿合作，以技術創新來推進貿易發展——可以為中國發展與其他中小歐洲國家經貿提供有益啟示。 關鍵詞：中比經貿發展模式；中小企業高科技合作；技術創新
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".