Bibliographic record
Abstract
The software currently available for analytical relief shading does not generally permit local adaptations of the light direction, the simulation of aerial perspective, and other necessary techniques developed for manual relief shading. To remedy this deficiency, a program for computer-assisted relief shading has been developed that allows users to locally adapt shading characteristics, permitting seamless interactive control over the entire process. The grey values of the image are determined by a combination of aspect-based shading for steep regions, diffuse reflection for lowlands, and a bright grey tone for flat areas. Furthermore, an algorithm for the simulation of aerial perspective is presented. Tests with the program have shown that, with minimal investment of time, the quality of analytically produced shaded relief can be improved significantly. Using the proposed techniques and software presented herein, experienced cartographers can transfer their manual relief-shading knowledge and experience to the digital realm. L'estompage est un moyen de visualisation du relief en cartographie qui peut ªtre produit de manire traditionnelle (dessin manuel) ou par des calculs informatiques. Les logiciels d'estompage existants actuellement ne permettent pas d'adaptations locales de direction de la lumire. La simulation de perspective arienne ou des modifications manuelles y sont galement impossibles. Pour combler ces lacunes, un programme d'estompage assist par ordinateur t dvelopp. Il permet l'utilisateur d'adapter localement les estompages gr¢ce un contr´le interactif de l'intgralit du processus. Les valeurs de gris du relief y sont dfinies partir d'une combinaison de deux mthodes : l'estompage des pentes raides est calcul partir de l'orientation du relief, et l'estompage des surfaces plus planes est calcul partir de la rflexion diffuse de la lumire. Par ailleurs, un nouvel algorithme pour la simulation d'effets de perspective arienne t utilis afin d'amliorer ces estompages. Contrairement d'autres programmes du mªme type, il s'est avr que les cartographes ayant une solide exprience manuelle des techniques d'estompage, peuvent ici facilement transfrer leurs connaissances au monde digital.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".