Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Passive monitoring of the data entering and leaving an enterprise network can support a number of forensic objectives. We have developed analysis techniques for NetFlow data that use behavioural identification and can confirm individual host roles and behaviours expressed as connection patterns. By looking at the way a given machine interacts with others, it is often possible to determine the role of the machine based solely on the network data. Host behaviours as characterized by NetFlow data are not stationary. Evolutionary changes occur as the result of new applications, computational and communications paradigms. Compromised machines often undergo changes in behaviour that range from subtle to dramatic. We use behavioural changes to identify role shifts and to trace the malicious or unintentional propagation of that change to other machines. Observed behavioural characteristics from over a year of traffic captures containing ordinary behaviours as well as a variety of compromises of interest are presented as examples for the forensics practitioner or researcher.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it