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Record W2159759252 · doi:10.1016/j.foar.2012.10.003

Building science or building physics

2012· article· en· W2159759252 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers of Architectural Research · 2012
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMathematics educationArt historyEngineeringVisual artsArchitectural engineeringHistoryPsychologyArt

Abstract

fetched live from OpenAlex

I like the ancient pattern, where and instead of one’s title one tells the name of one’s mentor. Three mentors shaped my professional life. The first one was in Warsaw, Poland, Prof. Bohdan Lewicki, whose books on concrete panels were translated in many languages. One day, after his class, he told me: ‘‘We need to evaluate hygrothermal performance of an experimental building with no-fine concrete,—if you would like to do it, I will provide you with all the money needed. From this day on, I have been learning Building Physics. My second mentor was Prof. Lars Eric Nevander in Lund, Sweden, one of the three Swedish professors who in 1972 introduced limit states method into the field of durability assessment, exactly 40 years before the first ISO standard did so. Lars Eric taught me that progress in construction depends on how strong is the continuum between industrial and academic domains in Building Physics. My third mentor was Prof. Neil Hutcheon known in Canada as the father of building science. It is only fair that I start writing my column with his definition of Building Science.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.101
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.064
GPT teacher head0.342
Teacher spread0.278 · 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