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Record W2765665524 · doi:10.1016/j.ifacol.2017.08.2376

Mixed-initiative system for tactical planning allowing real-time constraint insertions

2017· article· en· W2765665524 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

VenueIFAC-PapersOnLine · 2017
Typearticle
Languageen
FieldComputer Science
TopicAI-based Problem Solving and Planning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPlannerComputer scienceDashboardConstraint (computer-aided design)Decision makerOperations researchTime constraintValue (mathematics)Industrial engineeringMathematical optimizationArtificial intelligenceMachine learningEngineeringSoftware engineeringMathematics

Abstract

fetched live from OpenAlex

In complex industrial contexts, planning is a challenging problem. The companies can use two different approaches: planning can be carried out “manually” by a human planner or they can rely on a mathematical model to provide an optimal solution. In this paper, we introduce an Excel add-in allowing the decision-maker to generate their own interactive dashboard. The user can modify the value of some variables and all the other variables are updated in real-time. Moreover, we provide an algorithm to overcome to major drawback of the original approach.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.064
GPT teacher head0.303
Teacher spread0.239 · 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