Bibliographic record
Abstract
Welcome to the 2008 SIGGRAPH conference and to the August e-quarterly issue of "Computer Graphics". I am excited about the submissions in regards to both the breadth in content as well as the geographic location of the contributors, which is an indicator of how truly global the SIGGRAPH organization is. Murat Kurt and Muhammed Gökhan Cinsdikici at the International Computer Institute, Ege University, Turkey have written a paper on "bidirectional reflectance distribution functions" (BRDFs) and approaches to solving memory and measurement noise problems. Jonathan Amakawa, Instructor at The Art Institute of Pittsburgh, delves into preserving facts through fiction by researching the use of video game technology to archive Japanese culture as illustrated in his article "Exploring the World of 16th Century Japanese Castles and Samurai in Real-time 3D". VisFiles brings us another interesting article by way of Norway and Austria, this time about illustrative visualization, discussing digital and traditional techniques and technologies. Canadian Neil Schneider takes up the subject of popularizing 3D Stereoscopics in the "Members at work" section and has submitted a two part interview with the world renowned Dr. Robert Cailliau, Co-Developer of the WWW. Following the first Antics article written by founder Philip Swinstead, Brad Kolacinski has submitted the second in a series of three entitled "If You Animate It, They will Come", which presents examples of how 3D is being used in the classroom. Last but not least, don't forget to read the "calls for participation" by Rick Barry for the SIGGRAPH 2008 SpaceTime, Second Life Exhibition and by Anna Ursyn for The History of Computer Graphics and Digital Art Project.
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 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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.074 | 0.028 |
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".