{"id":"W4248597360","doi":"10.32920/ryerson.14648517.v1","title":"Choreographing architecture","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Architecture and Computational Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Kinesthetic learning; Architecture; Motion (physics); Movement (music); Empathy; Space (punctuation); Cognitive science; Computer science; Human–computer interaction; Psychology; Aesthetics; Artificial intelligence; Visual arts; Social psychology; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003875333,0.0002085529,0.0001876887,0.0001344327,0.00002830145,0.00008556084,0.0001823807,0.0001593335,0.0001604435],"category_scores_gemma":[0.000005008477,0.0001955703,0.0001600481,0.0001073198,0.000014525,0.00001507403,0.0001684601,0.0007003444,0.00001066316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001644183,"about_ca_system_score_gemma":0.00002846665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001038753,"about_ca_topic_score_gemma":0.00001962403,"domain_scores_codex":[0.9993031,0.00001859211,0.0001456148,0.0002174305,0.0001544873,0.0001607805],"domain_scores_gemma":[0.999615,0.00004273749,0.00001369162,0.0002446506,0.00002657717,0.00005730509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.644554e-7,0.000004162289,0.00002248503,0.0001269995,0.00009773596,0.00002027258,0.0002822995,0.9589257,0.0002257137,0.0002299585,0.001060891,0.03900299],"study_design_scores_gemma":[0.0006840759,0.00006625339,0.01604245,0.00126059,0.0002796871,0.0002474722,0.0003127358,0.6651322,0.01079142,0.2594894,0.04120517,0.004488569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03759868,0.001992005,0.9079254,0.0001195263,0.0007333955,0.0001345786,0.000005914111,0.0008917131,0.05059882],"genre_scores_gemma":[0.9537249,0.00007294655,0.04540996,0.0001712139,0.0002960846,0.00002930805,0.000123661,0.00004814392,0.0001238539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9161261,"threshold_uncertainty_score":0.7975126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00658548412635637,"score_gpt":0.1910760070501887,"score_spread":0.1844905229238324,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}