THE ISPRS STUDENT CONSORTIUM: SUSTAINING RELEVANCE AND CREATING SHARED VISIONS FOR THE YOUTH
Bibliographic record
Abstract
Abstract. The ISPRS Student Consortium (ISPRS SC) continues to engage the youth in many activities aligned with the mission and vision of ISPRS. For the term 2016 – 2020, the ISPRS SC strengthened its foundations through collaboration within the ISPRS Council and Technical Commission V, and increasing its presence in various ISPRS events. The Consortium Board introduced several changes in the organization: (1) re-designed the official logo, which was used in different communication and media, (2) revision of the Consortium’s Statutes, (3) continued the legacy of the summer schools through a new set of guidelines that coordinated all summer schools organized within ISPRS, (4) launched the Webinar Series, (5) repackaged the Newsletter into SpeCtrum, (6) introduction of two new awards, (7) hosting of a three-day Youth Forum in the ISPRS Congress and (8) the introduction of the ISPRS SC Student Chapters. A total of 13 issues had been published under SpeCtrum, two of which featured the ISPRS and an outstanding special issue on Women in Remote Sensing and Geospatial Information that received over 500 reads overnight. The SpeCtrum continued to seek experts, professors and contributors who willingly shared their work and inspire the youth. SpeCtrum had been publishing high quality articles and had been featuring outstanding scientists and researchers in the fields of remote sensing, photogrammetry and spatial information science. The Consortium also launched the Webinar Series and kicked off with an introduction on Google Earth Engine and followed by the applications of deep learning in remote sensing in 2020. For this term, a total of 16 summer schools were hosted across the globe, including one hosted under the ISPRS Education and Capacity Building Initiatives in 2018. The Consortium also partnered with international organizations such as Geo-informatics and Space Technology Development Agency, ASEAN Research and Training Center for Space Technology and Applications and the local chapters of the IEEE – Geosciences and Remote Sensing Society Young Professionals (IEEE – GRSS YP) in Brazil. The members of the Consortium had been increasing in the past year, especially with its increased presence in various social media platforms. The Consortium envisions a future, where the younger generation takes the lead and engages in relevant social and global issues and contributing significantly to the scientific community. As a student and youth organization, it aims to continue to develop more ways of knowledge transfer, capacity building and establishing professional networks to prepare students and young professionals for a future of collaboration and cooperation.
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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 | 0.080 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.037 | 0.027 |
| Open science | 0.005 | 0.061 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".