Message from 2013 International Symposium on Foundations of Open Source Intelligence and Security Informatics chairs
Bibliographic record
Abstract
The International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI 2013, Niagara Falls, ON, Canada, 26–27 August 2013) provides a unique international forum for academic researchers, government professionals and industrial practitioners to socialize, share their ideas, and exchange their data, knowledge, and expertise. Terrorism and crime threaten the international community and our society more than ever before. Criminal networks and terrorist groups that often operate globally try to hide their illegal activities by using advanced information and communications technology. They communicate easier and form global communities that are hard to track. Fortunately, resources like social media, event logs, phone call logs, web logs, and other time series data, constitute a rich source for knowledge discovery. There is a serious need for innovative techniques and tools capable of achieving the ultimate goal of early warning to help detecting, identifying and neutralizing the source of a threat. Motivated by this need with high social impact, research related to open source intelligence and security informatics is gaining momentum in academia, industry, law enforcement and intelligence agencies. Developing effective knowledge discovery methods, techniques and tools to combat crime and terrorism requires coordinated and intensified collaborations across these communities. After the careful review of submitted papers by 90 expert reviewers, about 20 papers were finally accepted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".