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Record W4292401392 · doi:10.1007/s44196-022-00112-6

Intelligent Decision Analysis and Applications

2022· article· en· W4292401392 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Computational Intelligence Systems · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsComputer scienceDecision analysisArtificial intelligenceMathematicsStatistics

Abstract

fetched live from OpenAlex

Big data, Internet, Internet of things, and cloud computing have profoundly affected decision paradigms and methods in various disciplines and application areas, ranging from business and management to finance and economics, decision sciences, system evaluation, forecasting, psychology, sociology, tourism, health, safety, engineering, smart city management, and environmental management. Intelligent computing technology and intelligent decision models are developed to meet the needs of academia and practitioners. This special issue of International Journal of Computational Intelligence Systems (IJCIS) entitled "Intelligent Decision Analysis and Applications" aims to provide a forum for some state-of-the-art research in this emerging field and outline new and important developments in fundamentals, approaches, models, and intelligent decision support systems with applications to different areas. Twelve papers have been selected for publication in this special issue. Below is a brief summary of these twelve papers.

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.

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 score0.981
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.324
Teacher spread0.278 · 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