A straightforward graphical user interface for basic and advanced signal processing of thermographic infrared sequences
Bibliographic record
Abstract
IR-View, is a free and open source <i>Matlab</i> software that was released in 1998 at the Computer Vision and Systems Laboratory (CVSL) at Université Laval, Canada, as an answer to many common and recurrent needs in Infrared thermography. IR-View has proven to be a useful tool at CVSL for the past 10 years. The software by itself and/or its concept and functions may be of interest for other laboratories and companies working in research in the IR NDT field. This article describes the functions and processing techniques integrated to IR-View, freely downloadable under the GNU license at http://mivim.gel.ulaval.ca. Demonstration of IR-View functionalities will also be done during the DSS08 SPIE Defense and Security Symposium.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".