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Record W4313441591 · doi:10.13033/isahp.y2022.064

2022 ISAHP Book of Abstracts/Schedule

2022· article· en· W4313441591 on OpenAlexaff

Bibliographic record

VenueISAHP proceedings · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSensory Analysis and Statistical Methods
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsScheduleComputer scienceOperating system

Abstract

fetched live from OpenAlex

Welcome to ISAHP 2022!It is a pleasure to welcome all members of our AHP/ANP community to our second virtual meeting.While we had decided to move the ISAHP in 2020 to a virtual meeting, at the time it was not apparent how successful it would be to host a meeting virtually!What we found is that it enabled researchers and practitioners from around the world to rapidly converge and share the latest accomplishments, concepts, and research in the application of AHP/ANP in an impactful, convenient, and low-cost manner.When my father, Dr. Thomas Saaty, passed away in 2017 the last thing he told our family was "always look forward, never look back."As a pioneer in planning he would have been a strong supporter of a virtual conference format, one in which we all get to leave behind the vestiges of the pandemic and "move forward" in our respective pursuits.I hope that you can appreciate the import of his statement and overall idea of "looking forward."I would also like to thank Rozann Saaty, my mother and the founder of the Creative Decisions Foundation (CDF).CDF provides funds to organize this symposium and also grants for scholars and students to attend this event.We also heartily thank our sponsors, Arama Consulting, Decision Lens, and The International Society of Multiple Criteria Decision Making, without which many of the scholarships would not have been available.This meeting, whose theme is "Decision-Making in Business Practice" is not only dedicated to Tom's memory and to his legacy but also to our desire to see this ground-breaking theory applied in actual practice, relevant to the most important decisions that organizations make in the world today.We also seek to recruit a new generation of AHP/ANP researchers and practitioners interested in promoting better decision making in an ever more ISAHP 2022 p. 13 complex world.Finally, I would like to express my recognition to all the members of the organizing committee: CDF president Rozann Saaty, program co-chairs Biesen Karpak, Marcel Minutolo and Elena Rokou, the head of the scientific committee Enrique Mu and Antonella Petrillo and our hard-working conference manager Lirong Wei.Without them this even would not have been possible.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.134
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.8660.775

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 head0.023
GPT teacher head0.248
Teacher spread0.224 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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