MétaCan
Menu
Back to cohort

Quantifying the Intangible, A Tool for Retrospective Protocol Studies of Sketching During the Early Conceptual Design of Architecture

2022· article· en· W4286384543 on OpenAlexaboutno aff
Jessica Bielski, Christoph Langenhan, Christoph Ziegler, Viktor Eisenstadt, Andreas Dengel, Klaus‐Dieter Althoff

Bibliographic record

VenueProceedings of the International Conference on Computer-Aided Architectural Design Research in Asia · 2022
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsSketchComputer scienceArchitectureHuman–computer interactionProtocol (science)Process (computing)Protocol analysisDesign educationSoftware engineeringProgramming language

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.169
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.032
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.169
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.006
Science and technology studies0.0020.003
Scholarly communication0.0050.010
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0270.005

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 head0.217
GPT teacher head0.403
Teacher spread0.186 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Computer-Aided Architectural Design Research in AsiaSame topicDesign Education and PracticeFrench-language works237,207