MétaCan
Menu
Back to cohort

Research of Inservice Arch Bridge Superstructure Damage Status and Evaluation Index System

2013· article· en· W2048277613 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

VenueApplied Mechanics and Materials · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEvaluation Methods in Various Fields
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsArchBridge (graph theory)Arch bridgeJudgementAnalytic hierarchy processEngineeringSuperstructureStructural engineeringForensic engineeringOperations research

Abstract

fetched live from OpenAlex

Scientific and integrated index system is a basic approach to accurately assess actual structure state of inservice arch bridge. It could provide clear evaluation guidance to assessment work of existing bridges. What is more, it is aimed to avoid or reduce erroneous and omission judgement phenomenon of bridge damage assessment by the grassroots-level maintenance workers. Based on summation of variety common damage in common arch bridges, this paper adopts AHP (analytic hierults are aimed to provide effective method and basis to long-term, persistent damage evaluaarchy process) method to establish arch bridge superstructure damage evaluation model with structure member (or component), the restion of inservice arch 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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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)0.0010.000

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 head0.059
GPT teacher head0.352
Teacher spread0.293 · 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