Bibliographic record
Abstract
It is our great pleasure to welcome all of you to 2019 International Conference on Environment and Ocean Engineering (ICEOE 2019) which was held on June 7-9, 2019 in Xiamen Ocean Vocational College, Xiamen, China. ICEOE 2019 is dedicated to issues related to Environment and Ocean Engineering. ICEOE 2019 is organized by Xiamen Ocean Vocational College and Xiamen University of Technology, assisted by International Society for Environmental Information Sciences (ISEIS), Hong Kong Chemical, Biological & Environmental Engineering Society (HKCBEES), Environment and Agriculture Society (EAS), Fujian Smart City Association. ICEOE 2019 is highlighted by several professional speakers. Prof. Caterina Valeo from University of Victoria, Canada; Prof. Yongping Li from Xiamen University Of Technology, China; Prof. Lixiao Zhang form School of Environment, Beijing Normal University, China; Prof. Guangwei Huang from Sophia University, Tokyo, Japan; Prof. R. J. (Dick) Haynes from The University of Queensland, St Lucia, Queensland, Australia; Prof. Gordon Huang from University of Regina, Canada had attended the conference as keynote speakers. There were five sub-sessions with different topics: Modeling of Environmental Systems, Environmental Pollution Control, Environmental Management and Planning, Workshop on Environment, Water and Energy, Forum on South-South Sustainable Development. It was a golden opportunity for students, researchers and engineers to interact with the experts and specialists to get their advice or consultation on technical matters, dissemination and marketing strategies. This proceeding presents a selection from papers submitted to the conference from universities, research institutes and industries. It has five chapters with topic: Coastal Engineering, Deep Sea Engineering, Ship Engineering, Utilization of Marine Resources, Water Pollution Control. All papers were subjected to peer-review by conference committee members and international reviewers. The papers were selected based on high quality and relevancy to the conference scope. We would also express our sincere gratitude to organizing committee and the volunteers who had dedicated their time and efforts in planning, promoting, organizing and helping the conference. Changping Chen Xiamen Ocean Vocational College, China 2019-09-20
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.541 | 0.379 |
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".