Special Issue on Situation Awareness in Intelligent Human-Computer Interaction for Time Critical Decision Making
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
The articles in this special section focus on situation awareness in intelligent human-computer interaction for critical decision making (HCI). HCI is recognized as an ctive field that focuses on the various interactions of human with machines. The HCI has been widely applied in multiple domains, such as artificial intelligence, computer vision, image and multimedia analysis, and cognitive and behavioral sciences. The objective of the HCI is to make the computer smart via receiving enough knowledge about the environment where it is deployed and reduce the human intervention aspect toward decision making. This enables development of high-end computers that are context aware and smart in making decisions with reference to the context. Situation awareness of an intelligent HCI will decide the success and application of the solution across the real world environment. The aim of this special issue is to provide a platform on the topic of situation awareness in intelligent HCI for time critical decision making.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.011 |
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