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Product Cost Determination

2015· other· en· W1529802785 on OpenAlexaff
Kashi R. Balachandran, Jeffrey L. Callen

Bibliographic record

VenueWiley Encyclopedia of Management · 2015
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicAdvanced Queuing Theory Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOutsourcingService (business)Product (mathematics)Center (category theory)Set (abstract data type)Cost allocationComputer scienceOperations managementBusinessOperations researchEconomicsEngineeringMarketingMathematics

Abstract

fetched live from OpenAlex

Abstract Allocation of costs of a commonly used service center by several jobs is an important aspect of determining product costs. Jobs that access a common service center cause delay to other jobs and this is captured in this article for developing a theoretically correct opportunity cost approach to cost allocation. The approach is used to determine the benefit obtained from setting up a capacity for the center to help in the determination of whether to outsource the service or to set up own facility.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.005

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 head0.011
GPT teacher head0.239
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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