Mapping of the Indoor Conditions by Infrared Thermography
Bibliographic record
Abstract
We present an instrumentation devoted to the mapping of indoor ambient conditions by an infrared camera. In addition to a measurement grid composed of several spherical sensors, an infrared camera is used to visualize and quantify the spatial distribution of the air temperature, the air speed, and the mean radiant temperature. A suitable procedure is developed so that from its temperature history recorded by the infrared camera, each sensor can measure, after solving an inverse heat transfer problem, all the three cited parameters. As the sensors are all imaged at the same time by the camera, an interpolation is done with the values they provide; the 2D distribution of each parameter is then obtained. By using a pair of stereoscopic cameras, it is possible to determine the 3D coordinates of each sensor of the measurement grid; consequently, the 3D mapping of the indoor ambient conditions is possible. Two steps are followed and allow us to achieve our goal: the validation of the performance of the sensor in terms of accuracy and reliability, and the validation of the complete experimental procedure which relies on digital image processing and on inverse heat transfer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".