Development of the AFRL CAESAR Web User Interface
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
<div class="htmlview paragraph">Civilian American and European Surface Anthropometry Resource (CAESAR) (<span class="xref">Robinette, et al., 2002</span>) is an anthropometric database containing the latest civilian population survey of three countries representing the NATO countries: the United States of America, The Netherlands, and Italy. There are many potential applications for the CAESAR database in the anthropometry, ergonomics, and biometrics fields because it provides individual and standardized one-mode data instead of summarized population information such as percentiles. However, people are not using CAESAR more frequently because it is too difficult to access at present. To facilitate the sharing of this valuable resource, the CARD Lab (Computerized Anthropometric Research and Design Laboratory) in the Air Force Research Laboratory has been developing a web application, ARIS (Anthropometry Research Information Systems), to offer CAESAR data search and analysis as well as raw data visualization and extraction. ARIS consists of two components. The front-end user interface was designed for two groups of potential users. An atlas-type graphics interface targets casual users, and a menu-driven detailed search interface satisfies the needs of advanced users. The back-end database was designed to handle not only the CAESAR database but also other anthropometric databases collected by the CARD Lab over the years. The objective is to provide a new capability to make the right anthropometric information available to anyone, anywhere.</div>
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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