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Record W2056298295 · doi:10.7202/044075ar

Simulation informatisée en humanités et sciences sociales

2010· article· fr· W2056298295 on OpenAlexvenueno aff
Enrico Scalas

Bibliographic record

VenueNouvelles perspectives en sciences sociales · 2010
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicComplex Systems and Time Series Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Ce texte court sur les simulations dans les sciences humaines et sociales est consacré aux simulations multi-agents. Les ingrédients d’une simulation multi-agents sont essentiellement au nombre de deux : agents et interactions. Les Agents avec leurs propriétés interagissent entre eux et les interactions peuvent être soit directes soit indirectes. Par analogie avec les systèmes physiques, la pertinence de l’équilibre statistique en économie peut être aussi analysée.

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)0.007
metaresearch head score (Gemma)0.030
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 score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0010.003
Scholarly communication0.0070.005
Open science0.0020.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0150.002

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 head0.091
GPT teacher head0.343
Teacher spread0.252 · 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
Published2010
Admission routes1
Has abstractyes

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