Bibliographic record
Abstract
The performance of the MaxRGB illumination-estimation method for color constancy and automatic white balancing has been reported in the literature as being mediocre at best; however, MaxRGB has usually been tested on images of only 8-bits per channel. The question arises as to whether the method itself is inadequate, or rather whether it has simply been tested on data of inadequate dynamic range. To address this question, a database of sets of exposure-bracketed images was created. The image sets include exposures ranging from very underexposed to slightly overexposed. The color of the scene illumination was determined by taking an extra image of the scene containing 4 Gretag Macbeth mini Colorcheckers placed at an angle to one another. MaxRGB was then run on the images of increasing exposure. The results clearly show that its performance drops dramatically when the 14-bit exposure range of the Nikon D700 camera is exceeded, thereby resulting in clipping of high values. For those images exposed such that no clipping occurs, the median error in MaxRGB's estimate of the color of the scene illumination is found to be relatively small.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".