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Record W4241080841 · doi:10.32920/14641956.v1

Mereotopology for product modeling

2021· preprint· en· W4241080841 on OpenAlexaff
Filippo A. Salustri

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceTask (project management)Product (mathematics)New product developmentProduct designSoftware engineeringSystems engineeringManagement scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

Mereotopology is the branch of logic that treats the qualitative formalisation of parthood and connection relations between entities. Although it has apparently not yet found use in spatial reasoning for designed product modelling, the author proposes that it is well suited to the task. This paper introduces mereotopology and discusses some of the principles guiding the development of design mereotopology (DMT), a logic being developed by the author for product modelling. Typical MT logics cannot be applied directly to engineering applications because they assume a "common sense" approach, whereas design requires a more strict "engineering sense." DMT can provide a framework for improved understanding of product modelling knowledge and will lead to better computer-based aids to manipulate that knowledge.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0030.007
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.072
GPT teacher head0.310
Teacher spread0.238 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1
Published2021
Admission routes1
Has abstractyes

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