LATEST DEVELOPMENTS OF THE ISPRS STUDENT CONSORTIUM
Bibliographic record
Abstract
The International Society for Photogrammetry and Remote Sensing (ISPRS) Student Consortium (SC) is a network for young professionals studying or working within the fields of photogrammetry, remote sensing, Geographical Information Systems (GIS), and other related geo-spatial sciences. The main goal of the network is to provide means for information exchange for its young members and thus help promote and integrate youth into the ISPRS. Over the past four years the Student Consortium has successfully continued to fulfil its mission in both formal and informal ways. The formal means of communication of the SC are its website, newsletter, e-mail announcements and summer schools, while its informal ones are multiple social media outlets and various social activities during student related events. The newsletter is published every three to four months and provides both technical and experiential content relevant for the young people in the ISPRS. The SC has been in charge or at least has helped with organizing one or more summer schools every year. The organization's e-mail list has over 1,100 subscribers, its website hosts over 1,300 members from 100 countries across the entire globe, and its public Facebook group currently has over 4,500 joined visitors, who connect among one another and share information relevant for their professional careers. These numbers show that the Student Consortium has grown into a significant online-united community. The paper will present the organization’s on-going and past activities for the last four years, its current priorities and a strategic plan and aspirations for the future four-year period.
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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 | 0.029 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.017 |
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".