Quick Profiler (QuiP): a friendly tool to extract roughness statistical parameters using a needle profiler
Bibliographic record
Abstract
AbstractQuiP is a graphical user interface (GUI) developed in MATLAB to extract and analyze soil surface profile measurements obtained from a needle profiler in a few minutes. Surface roughness parameters can be extracted from any needle profiler with simple modifications to the tool. QuiP calculates many statistics useful in radar remote sensing while generating the profiles. Furthermore, a QuiP function can be used to join several profiles. Long profiles can therefore be created from a short profiler (e.g., 1 m) that is easier to carry and handle in the field. Extraction of profiles by QuiP is repeatable and therefore reduces user's errors from data processing.QuiP est une interface graphique d'utilisation (GUI) développé sous MATLAB, qui permet d'extraire et d'analyser les profils de rugosité de surface de profilomètres à aiguilles en quelques minutes. De simples modifications au profilomètre permettent l'utilisation de QuiP et ainsi d'analyser les profils de manière efficaces. Des paramètres statistiques utilisés en télédétection radar sont automatiquement calculées par QuiP. De plus, QuiP permet de joindre plusieurs profils et ainsi de recréer des profils de plusieurs mètres en utilisant un profilomètre de plus petite taille (i.e., 1 m) qui est plus facile à manipuler et à transporter. La répétabilité de l'extraction avec QuiP est démontrée, ce qui réduit les erreurs liées à l'utilisateur.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".