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Record W2547720744 · doi:10.3963/jmpm.v4i2.206

Exploratory study of success factors for research and development projects run by SMEs in Quebec linked to secondary and tertiary aluminum production

2016· article· en· W2547720744 on OpenAlexaffabout
Caroline Durand, Christophe Leyrie, Julien Bousquet

Bibliographic record

VenueJournal of Modern Project Management · 2016
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsStakeholderContext (archaeology)Exploratory researchProduction (economics)BusinessProject managementSubject (documents)Operations managementProcess managementEngineeringPolitical sciencePublic relationsComputer scienceSociologyEconomicsLibrary scienceGeographySocial scienceSystems engineering

Abstract

fetched live from OpenAlex

Despite extensive literature on the subject of success, there is no consensus. However, it is accepted that success is evaluated by certain criteria and that it is dependent on success factors. Moreover, these concepts can vary according to the type of company, project and especially the stakeholder evaluating them. Within this context, the present study will discuss these criteria and factors as applied to projects run by SMEs working in the secondary and tertiary aluminum industry. The aim of the study is to help create a generic model applicable within the specific field of R&D projects submitted to the Centre quebecois de recherche et de developpement de l’aluminium (Aluminum Research & Development Center of Quebec) .

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.063
GPT teacher head0.309
Teacher spread0.246 · 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 designQualitative
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

Citations2
Published2016
Admission routes2
Has abstractyes

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