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Record W2724113590 · doi:10.13140/rg.2.2.11830.29769

A simple pooling model with application in the feed industry and its global solution analysis

2017· preprint· en· W2724113590 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

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2017
Typepreprint
Languageen
FieldMathematics
TopicAdvanced Optimization Algorithms Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSimple (philosophy)PoolingEconometricsComputer scienceIndustrial organizationEconomicsMathematical economicsBusinessMathematicsArtificial intelligenceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

We present a specific pooling model which, while simple, still uses bi-linear objective and constraints. An absolute lower bound is available for this model. We conjecture that any local solution is a global minimizer for this simple instance. We will motivate its usage within a feed industry application. We will then present several experiments to support our conjecture. Since the dimension is in the hundreds, no global solver is able to solve it. Among arguments to support our conjecture is the fact that for smaller instances solvable by global solvers, the solutions computed by local solvers are indeed global.

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)0.005
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.043
GPT teacher head0.331
Teacher spread0.288 · 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