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Record W2760324339 · doi:10.1002/sres.2488

Strategies for Discovering Scientific Systems Principles

2017· article· en· W2760324339 on OpenAlexaff
David Rousseau

Bibliographic record

VenueSystems Research and Behavioral Science · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsSurrey Place Centre
FundersUniversity of Oregon
KeywordsAnalogySystems scienceManagement scienceScientific discoveryComputer scienceSystems theorySystems thinkingComplex systemEngineering ethicsEpistemologyData scienceCognitive sciencePsychologyEngineeringArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

The development of a general theory of systems has been impeded by lack of progress with identifying and refining scientific general systems principles that could underpin the systematic discovery of systems laws and development of predictive systems theories. This paper discusses a model of the nature, roles and developmental pathways of principles in science generally and by analogy suggests ways in which scientific systems principles might be identified and leveraged by systems science. Eight strategies for such research are identified, and preliminary results of a first pilot project are presented. Copyright © 2017 John Wiley & Sons, Ltd.

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)0.027
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.027
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.034
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.003
Science and technology studies0.0030.016
Scholarly communication0.0110.015
Open science0.0040.009
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0140.003

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 head0.729
GPT teacher head0.597
Teacher spread0.133 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations13
Published2017
Admission routes1
Has abstractyes

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