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Record W2943270635 · doi:10.34196/ijm.00034

Editorial special issue on ‘methodological issues in microsimulation’

2009· article· en· W2943270635 on OpenAlexaboutno aff
Gijs Dekkers

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsnot available
Fundersnot available
KeywordsMicrosimulationEconomicsRegional scienceSociologyEngineeringTransport engineering

Abstract

fetched live from OpenAlex

This special issue is one of several reporting on papers presented during the 2nd General Conference of the International Microsimulation Association (IMA): “Microsimulation: Bridging Data and Policy”, Statistics Canada, Ottawa, Canada, June 8th to 10th, 2009. The papers all deal with methodological issues and are selected on the basis of innovativeness and relevance for all IJM readers.

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)0.010
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.028
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.044
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0070.004
Open science0.0030.002
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0280.012

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 head0.252
GPT teacher head0.483
Teacher spread0.231 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations2
Published2009
Admission routes1
Has abstractyes

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