MétaCan
Menu
Back to cohort
Record W7099353828

Transportation Association of Canada Saskatoon, Saskatchewan

2015· article· en· W7099353828 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)Work (physics)Decision support systemSelection (genetic algorithm)Management systemAssociation (psychology)State (computer science)Information system
DOInot available

Abstract

fetched live from OpenAlex

2 With the aging of its infrastructure, Canada is facing a critical problem to deal with the complex and fragmental issues existing in current infrastructure management. Because Bridge Management Systems (BMSs) are not used universally in Canada, this paper aims at reviewing the current state of BMSs in Canada and suggesting an initiative to build a Canadian National Bridge Inventory. The Bridge Expert Analysis and Decision Support (BEADS) system currently used in Alberta is different from the BMSs of other provinces in its system structure and scope. The BEADS is an important part of a comprehensive system-- Transportation Infrastructure Management System (TIMS). The Ontario BMS integrates the deterioration model, cost model, and business rules for treatment selection and costing, and an analytical framework for calculating and representing information relevant to the decision at hand. The Quebec BMS has three main models (Deterioration Model, Treatment Model, and Cost Model) that are used to create work alternatives at the element, project, and program levels. Pontis is used as the BMS in Manitoba. Pontis can support the complete bridge management cycle, including bridge

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 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.190
Teacher spread0.181 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicSingle-cell and spatial transcriptomicsFrench-language works237,207