MétaCan
Menu
Back to cohort
Record W4318773910 · doi:10.1016/j.cie.2023.109066

Infectious waste management during a pandemic: A stochastic location-routing problem with chance-constrained time windows

2023· article· en· W4318773910 on OpenAlexafffund
Saeed Tasouji Hassanpour, Ginger Y. Ke, Jiahong Zhao, David M. Tulett

Bibliographic record

VenueComputers & Industrial Engineering · 2023
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsMathematical optimizationPandemicComputer scienceInteger programmingOperations researchLinear programmingService (business)Budget constraintConstraint (computer-aided design)Routing (electronic design automation)Coronavirus disease 2019 (COVID-19)EngineeringMathematicsBusinessEconomicsComputer networkMedicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.010
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0040.004
Open science0.0040.003
Research integrity0.0080.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.223
Teacher spread0.203 · 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

Citations42
Published2023
Admission routes2
Has abstractno

Explore more

Same venueComputers & Industrial EngineeringSame topicHealthcare and Environmental Waste ManagementFrench-language works237,207