Hong Kong Student Science Project Competition 2021
Bibliographic record
Abstract
The Hong Kong Student Science Project Competition (HKSSPC) promotes the interest in science and technology among youth, develops their creativity and critical thinking skills through an innov ative application of science and technology, and ignites their passions and career interests in these areas. This year, the HKSSPC was organized by The Hong Kong Federation of Youth Groups, the Education Bureau, the Hong Kong Science Museum, and the Hong Kong Science and Technology Parks Corporation. Furthermore, it was supported by the Innovation and Technology Commission and the Hong Kong Young Academic of Sciences. We extend our thanks to all these groups for making this year’s competition a success. STEM Fellowship collaborated with the HKSSPC Secretariat to provide youth from Hong Kong with the unique opportunity to submit their work in the STEM Fellowship Journal. This year’s theme was “Inspiration from Living - Innovation from Science” with an emphasis on United Nations’ Sustainable Development Goals. The broad scope of the competition allowed participants to submit their work in a variety of areas such as water pollution, nanoparticles, artificial intelligence systems, agriculture, environmental health, plastics, waste reduction, and many more. We are pleased to share the creativity and ambitious drive for research demonstrated by HKSSPC’s participants in these proceedings. We would like to congratulate every passionate individual who participated in the HKSSPC this year and wish them the best in their future STEM-related endeavours.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.263 | 0.103 |
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".