Collaborative Innovation in International R&D Among SMEs——The Case of CIIRDF
Bibliographic record
Abstract
Canada-Israel Industrial R D Fund(CIIRDF) is a Canada and Israel to promote small and medium enterprises of both countries to carry international cooperation in industrial technology innovation program.The fund is conditional investment-oriented business plan,Canada and Israel through the promotion of small and medium-sized co-operation between the two countries cooperation in industrial R D and profits,and fund the initiative will help enterprises to establish cooperation between the two countries as an important task.CIIRDF learn from the practice of agriculture and small and medium enterprises in China of going out should be innovative mechanisms of cooperation between the Government,working closely with the linkage of foreign aid to strengthen the information and intermediary services.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".