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Record W4400410871 · doi:10.1109/mits.2024.3401536

An Introduction to the Smart Urban Mobility Laboratory at University of South Florida [ITS Research Lab]

2024· article· en· W4400410871 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIEEE Intelligent Transportation Systems Magazine · 2024
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringAeronauticsComputer science

Abstract

fetched live from OpenAlex

Founded in 1956, the University of South Florida (USF) is a high-impact global research university serving more than 50,000 students at its campuses in Tampa, St. Petersburg, and Sarasota Manatee, in Florida, USA. In early 2023, USF accepted an invitation to join the Association of American Universities (AAU), a prestigious group of the 71 leading research institutions in the United States and Canada. In 2018, USF was designated by the Florida Board of Governors as a “preeminent state research university,” which recognizes its high performance and strong trajectory toward national excellence. USF is the fastest-growing public university in the United States in the last 10 years, rising 54 slots, and is now ranked 46 in the country among the 209 public universities. USF is ranked 89 among national universities, according to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U.S. News &amp; World Report</i>, rising 92 spots in the past 10 years as well.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.025
GPT teacher head0.251
Teacher spread0.226 · 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