Measures for reducing the vehicle fleet of Komunala Nova Gorica company, with an estimation of cost-cuts and related improvements
Why this work is in the frame
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Bibliographic record
Abstract
Magistrsko delo obravnava možnosti za zmanjševanje voznega parka podjetja Komunala Nova Gorica d.d. in ima dva cilja. Primarni cilj je zniževanje stroškov odvoza odpadkov, posredni cilj pa je povečevanje deleža ločeno zbranih odpadkov, saj je delež ločeno zbranih odpadkov glede na prihajajoče uredbe prenizek. Med ukrepi, s katerimi želimo doseči navedena cilja, najprej obravnavamo spremembo kontejnerskih mest v ekološke otoke in navodila za pravilno izvajanje del v enoti za zbiranje in odvoz odpadkov. V osrednjem delu pa se posvetimo izboljševanju transportnih poti, ki jih ob primerni izvedbi omogoča uporaba navigacijskih naprav. Na podlagi analiz stanja pred ukrepi in po njih so ovrednoteni učinki obravnavanih ukrepov. Rezultat je zmanjšanje števila potrebnih smetarskih vozil za odvoz mešanih odpadkov v podjetju Komunala Nova Gorica d.d. in povečan delež ločeno zbranih odpadkov v občinah, v katerih deluje to podjetje.
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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 | 0.000 |
| 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