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Record W3119454465 · doi:10.5951/mt.96.4.0286

Where Is the Highest Point on the Roof of a Shed?

2003· article· en· W3119454465 on OpenAlexaff
Ysbrand de Bruyn

Bibliographic record

VenueMathematics Teacher Learning and Teaching PK-12 · 2003
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsGlaxoSmithKline (Canada)
Fundersnot available
KeywordsSimplex algorithmSimplexRoofLinear programmingPoint (geometry)MathematicsInterior point methodPlane (geometry)Computer scienceCombinatoricsMathematics educationEngineeringGeometryStructural engineeringAlgorithm

Abstract

fetched live from OpenAlex

Some time ago, a freshman engineering student returned to the high school where I taught and described to me some of his struggles with university mathematics. The simplex method of linear programming was one topic that we discussed. This student could perform the mechanics of the simplex method—finding pivot columns, pivot rows, and row reductions; however, he confessed that he had no idea why the simplex method worked to find the maximum point. Moreover, he could not connect the theorems that his professor proved in the lectures with the simplex method. So I asked him this question: “Where is the highest point on the roof, excluding the overhang, of a shed with a plane, but sloping, roof?” He looked at me and was clearly wondering why sheds had anything to do with linear programming.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.842
Threshold uncertainty score0.497

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.214
Teacher spread0.201 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2003
Admission routes1
Has abstractyes

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