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Record W2806720832

AN INTERACTIVE WORKBENCH FOR MONITORING , IDENTIFICATION AND CALIBRATION OF BUILDING ENERGY MODELS

2012· article· en· W2806720832 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

VenueProceedings of SimBuild · 2012
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWorkbenchMATLABComputer scienceCalibrationIdentification (biology)Building energy simulationControl engineeringSet (abstract data type)Systems engineeringSimulationSoftware engineeringEfficient energy useEngineeringData miningOperating systemEnergy performanceProgramming languageVisualization
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a concept and main capabilities of the Matlab-based Building Energy Modeling (BEM) Workbench developed at Ryerson University (Toronto, Canada). The workbench was designed as an interactive tool intended to facilitate and to provide common media for data processing tasks related to various building energy modeling procedures such as (i) on-site data monitoring, (ii) preparation of input data and analysis of simulation results, (iii) validation, verification and calibration of building energy models and (iv) estimation of building thermal parameters. To illustrate the use of the BEM-Workbench several working scenarios are presented. Known inputs from literature methodologies of building thermal parameter estimation were implemented into the workbench to demonstrate one of its purposes as a hypothesis testing tool. Another scenario was introduced to show how the workbench can be used to analyze a buildings model’s dynamic behavior, a critical step in the model’s calibration procedure. Programmatically, the workbench is configured as a set of Matlab GUI components and functions with capability to further expand its functionality.

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)0.000
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 score0.272
Threshold uncertainty score0.415

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 communication0.0000.002
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 head0.013
GPT teacher head0.236
Teacher spread0.224 · 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