An eye-hand system for automated paper recycling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Presents a robotic system used for detection, sorting and grading of paper objects as a part of an automated paper recycling system. The system uses stereo vision to estimate in real time the spatial position of moving objects on a conveyor to be picked by the robot arm. It was proved in the literature that stereo vision may be successfully used to estimate position of moving objects, with a priori known shape, and generate commands to a robot arm for picking up the object. A special computing architecture is introduced for performing the task in real time. A vector of geometric and textural features is used for sorting the paper, according to its grade. The grading process uses color vision and additional contact ultrasonic sensors. A new data fusion paradigm, based on supervised learning, is used. The data fusion algorithm combines stereo vision and ultrasonic sensors to detect and grade paper objects.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it