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Record W1984787390 · doi:10.1109/ieem.2009.5373042

A comparative study to estimate costs at Bombardier Aerospace using regression analysis

2009· article· en· W1984787390 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor Technologies Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsLinear regressionRegression analysisComputer scienceParametric statisticsReliability (semiconductor)CredibilityAerospaceLinear modelRegressionGeneral linear modelStatisticsEngineeringMathematicsMachine learning

Abstract

fetched live from OpenAlex

The purpose of this research is to develop a target cost model for the Main Landing Gear at Bombardier Aerospace. This will offer a cost understanding at the early conception stage. The study uses a comparative analysis between a linear and a non-linear parametric model in order to determine which estimation method will increase the credibility of the cost estimate. The reliability of the models will be validated by two different methodologies to determine which parameter(s) become significant and will therefore be used to determine the cost. These methodologies are the analysis of variance and path analysis. It was found that the non-linear regression analysis achieves a lower level of error when comparing it to the linear regression.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.412
Teacher spread0.364 · 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

Quick stats

Citations5
Published2009
Admission routes1
Has abstractyes

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