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Record W4318761575 · doi:10.1111/poms.13755

Issue Information

2023· paratext· en· W4318761575 on OpenAlexfundno aff

Bibliographic record

VenueProduction and Operations Management · 2023
Typeparatext
Languageen
FieldSocial Sciences
TopicEarthquake and Disaster Impact Studies
Canadian institutionsnot available
FundersUniversity at BuffaloUniversity of North Carolina at Chapel HillUniversity of Colorado BoulderXiamen UniversityUniversiteit van TilburgCollege of Engineering, Michigan State UniversityTechnische Universität MünchenShanghai Jiao Tong UniversityNanyang Technological UniversityCardiff UniversityWilfrid Laurier UniversityUniversity of OregonUniversity of South CarolinaUniversity of North Carolina WilmingtonGeorgia State UniversityArizona State UniversityTulane UniversityEidgenössische Technische Hochschule ZürichOhio State UniversityNational University of SingaporeMichigan State UniversityBoston CollegeWashington University in St. LouisXiamen University of TechnologyRijksuniversiteit GroningenPurdue UniversitySouthern Methodist University
KeywordsComputer scienceBusiness

Abstract

fetched live from OpenAlex

Preparedness with a system integrating inventory, capacity, and capability for future pandemics and other disasters

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)0.002
metaresearch head score (Gemma)0.010
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 score0.108
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0020.001
Scholarly communication0.0110.004
Open science0.0020.003
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.8920.857

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 head0.028
GPT teacher head0.326
Teacher spread0.298 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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