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Record W7070412176

Optimering av staplarrobot

2012· other· sv· W7070412176 on OpenAlexaboutno aff

Bibliographic record

VenueTheseus (Ammattikorkeakoulujen) · 2012
Typeother
Languagesv
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Period (music)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Detta examensarbete behandlar optimering av en lastpallsstaplare som byggs av Mikrometalli. Lastpallsstaplaren används inom lastpallsindustrin och kan användas för att ta emot färdiga lastpallar från en arbetslinje och stapla dessa i en stapel, som sedan kan avlägsnas med t.ex. en truck. Arbetets huvudpunkter var byte av styrsystem, förbättring av funktionsprincipen, konstruktion av elcentral och planering av en ny elcentral med nya komponenter. Orsaken till bytet av styrsystem var att det gamla styrsystemet var dyrt och omodernt. Dessutom fanns det intresse av att använda en pekskärm i stället för en LCD-panel, som använts tidigare. Målet är att få lastpallsstaplare som fungerar på samma sätt som den gamla. Examensarbetet inleds med beskrivning av funktionssättet för lastpallsstaplaren, varefter en teori för de olika komponenterna följer. Till sist gås igenom planeringen och konstruktionen av centralen. Även maskinsäkerhet behandlas. Som slutresultat skapades en fungerande elcentral med ett nytt styrsystem och pekskärm som skall programmeras. Dessutom har ritningarna uppdaterats och en ny central planerats. Samtidigt har en kostnadsberäkning gjorts för de olika komponenterna.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0450.016

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 head0.030
GPT teacher head0.272
Teacher spread0.242 · 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 designSimulation or modeling
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
Published2012
Admission routes1
Has abstractyes

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