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Record W7135808160

The Analysis of Putting Logistics in to Practice in Magna Cartech in České Velenice

2009· dissertation· cs· W7135808160 on OpenAlexaboutno aff
Růžena VAŇKOVÁ

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2009
Typedissertation
Languagecs
FieldEngineering
TopicTransport and Logistics Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Production (economics)BachelorScheduleProduct (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

My bachelor work is focused on the firm Magna Cartech in České Velenice. Its activity consists mainly of the production of stampings for world car factories. Magna Cartech is a member of the supra-national Canadian concern called Magna International Inc., which is one of the world´s biggest purveyors of motor parts. Magna develops and produces components, systems and complete modules. Magna Cartech in České Velenice is included in the Cosma Division. Its production schedule is based on stamping and welding of metal parts for bodies and undercarriages. My work deals with both the slenderness of production and logistics in this firm, and especially one concrete product named TRAVERSE ARR PAVILLON ASS, which is produced for the French firm Peugeot. It deals with the material flow from the suplier to the dispatch to the customer. My bachelor work also notices the contemporary economic depression {--} especially Peugeot in the connection to Magna Cartech. The results of the research and potential suggestions for improving are always mentioned at the end of each chapter. The whole enumeration is summarized in the conclusion of the whole work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.011
Science and technology studies0.0040.006
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.007
GPT teacher head0.265
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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