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Record W1536700475

Decision-making of highway emergency rescue based on CBR

2010· article· en· W1536700475 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

VenueChinese Control Conference · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSafety and Risk Management
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsEmergency rescueCase-based reasoningComputer scienceProcess (computing)Matching (statistics)Service (business)Status quoFunction (biology)Operations researchPlan (archaeology)Emergency managementTransport engineeringEngineeringArtificial intelligenceBusinessMathematics
DOInot available

Abstract

fetched live from OpenAlex

This paper introduces the status quo of decision-making of highway emergency rescue, and takes the case-based reasoning (CBR) method into the decision-making process. By analyzing highway emergency classification and rescue measures, the paper designs a model of decision-making on emergency rescue based on CBR, and every module function is elaborated, thus formulating the mathematical method that realizes the case description, the case search and the case similarity judgment. The paper also proposes a modificatory idea to non-matching counter plan. Simulation result confirms that this method can play a good decision-making role in the highway emergency rescue service.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.248
Teacher spread0.239 · 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