Bibliographic record
Abstract
TIM (The Interactive METATOY) is a ray-tracing program specifically tailored towards our research in METATOYs, which are optical components that appear to be able to create wave-optically forbidden light-ray fields. For this reason, TIM possesses features not found in other ray-tracing programs. TIM can either be used interactively or by modifying the openly available source code; in both cases, it can easily be run as an applet embedded in a web page. Here we describe the basic structure of TIMʼs source code and how to extend it, and we give examples of how we have used TIM in our own research.Program title: TIMCatalogue identifier: AEKY_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEKY_v1_0.htmlProgram obtainable from: CPC Program Library, Queenʼs University, Belfast, N. IrelandLicensing provisions: GNU General Public LicenseNo. of lines in distributed program, including test data, etc.: 124 478No. of bytes in distributed program, including test data, etc.: 4 120 052Distribution format: tar.gzProgramming language: JavaComputer: Any computer capable of running the Java Virtual Machine (JVM) 1.6Operating system: Any; developed under Mac OS X Version 10.6RAM: Typically 145 MB (interactive version running under Mac OS X Version 10.6)Classification: 14, 18External routines: JAMA [1] (source code included)Nature of problem: Visualisation of scenes that include scene objects that create wave-optically forbidden light-ray fields.Solution method: Ray tracing.Unusual features: Specifically designed to visualise wave-optically forbidden light-ray fields; can visualise ray trajectories; can visualise geometric optic transformations; can create anaglyphs (for viewing with coloured “3D glasses”) and random-dot autostereograms of the scene; integrable into web pages.Running time: Problem-dependent; typically seconds for a simple scene.References:[1]JAMA: A Java matrix package, http://math.nist.gov/javanumerics/jama/.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.612 | 0.640 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".