Automatic Generation of Time-lapse Animations
Bibliographic record
Abstract
A simple system for the automatic generation of time-lapse animations has been created at the Aerodynamics Laboratory of the Institute for Aerospace Research, National Research Council of Canada (NRC). The system consists of two small Perl programs and a static web page, and relies heavily on two open source software packages: LWP::Simple, and ImageMagick. The first program, tlget.pl, runs for several hours each weekday and is responsible for the periodic acquisition (and storage) of images from a webbased camera. The second program, tlmpeg.pl, is responsible for the conversion of groups of JPEG format images into MPEG format animations. Typically, tlmpeg.pl is executed each weekday night, and generates three animation files, one from the past day's images, one from the past week's images, and one from the past month's images. A static web page has been created to display the image most recently acquired by tlget.pl, and to provide links to each of the three animation files most recently generated by tlmpeg.pl.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".