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Record W2625059566 · doi:10.18260/1-2--7447

Systematic Conceptualizing … A Case Study

2020· article· en· W2625059566 on OpenAlexaff
W. Ernst Eder

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicModeling, Simulation, and Optimization
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsBARGESession (web analytics)Task (project management)Computer scienceProcess (computing)Stage (stratigraphy)Engineering design processOperations researchIndustrial engineeringSystems engineeringEngineeringMechanical engineeringProgramming languageMarine engineeringWorld Wide WebGeology

Abstract

fetched live from OpenAlex

Just over a year ago, I was given a design taska gangway for the Caravan Stage Barge. Several restrictive requirements were stated, e.g.: 0.7 m (28") wide; two lengths (3 m or 10 ft, and 6 m or 20 ft reach from barge to land) should be readily available from the unit, but maximum length for storage should be no more than 3 m (10 ft); minimum weight and thickness were desirable.

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)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0070.012
Scholarly communication0.0070.008
Open science0.0030.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.181
GPT teacher head0.365
Teacher spread0.184 · 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 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
Published2020
Admission routes1
Has abstractyes

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