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Record W7019826234

International Product Safety - firewood processors : case Ylistaron Terästakomo Oy

2007· other· en· W7019826234 on OpenAlexaboutno aff

Bibliographic record

VenueTheseus (Ammattikorkeakoulujen) · 2007
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDirectiveEuropean unionFirewoodProduct (mathematics)LabellingSafety standards
DOInot available

Abstract

fetched live from OpenAlex

The aim of this bachelor's thesis was to investigate international product safety in general, but the focus point is on firewood processors. This thesis presents the European Union directive 98/79/EY which concerns the machine safety requirements in the area of the European Union. This directive has several standards which concern various aspects of machinery and their safety from technical aspects to safety labelling. This bachelor's thesis defines the industrial safety instructions and special safety labelling concerning particularly firewood processors. This thesis compares the different aspects of safety requirements of firewood processors between the European Union and the USA and between the European Union and Canada. Ylistaron Terästakomo Oy is a company which has many export operations in Europe, in the USA and in Canada. It would be really beneficial for them to know the various safety requirements concerning the safety regulations of exporting their firewood processors and when they are categorized as being safe in the different market areas, although the company already possesses the CE- and GS-certificates. The biggest difference between Europe, the USA and Canada is in the safety labelling of the products. This safety labelling contains mainly clear, informative pictures with a few describing words. Especially the USA has a more strict labelling policy than the European Union. On the other hand, in Canada the regulations vary even between provinces.

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)0.002
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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0250.003

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.

Opus teacher head0.022
GPT teacher head0.285
Teacher spread0.263 · 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 designCase report
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
Published2007
Admission routes1
Has abstractyes

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