{"id":"W4386699234","doi":"10.32920/24114480.v1","title":"Master of Architecture Studio in Critical Practice: Pale Blue Dot","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Architecture, Modernity, and Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Studio; Architecture; Design studio; Critical practice; Metropolitan area; Politics; Sustainability; Critical thinking; Sociology; Architectural engineering; Engineering; Political science; Visual arts; Art; Pedagogy; History; Social science; Ecology; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003785059,0.0003612011,0.0005395816,0.000321166,0.00002473013,0.00003927798,0.0003374621,0.0003944823,0.0001089541],"category_scores_gemma":[0.0005510937,0.0003261617,0.0001336368,0.0001417433,0.00009040071,0.00004713217,0.0005029244,0.00162183,0.00007351582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005482905,"about_ca_system_score_gemma":0.00005856838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000100873,"about_ca_topic_score_gemma":0.0003390495,"domain_scores_codex":[0.99819,0.0001332981,0.0004898209,0.0004212965,0.0003647305,0.0004008585],"domain_scores_gemma":[0.9982114,0.0009751974,0.000044669,0.0005990963,0.00007095383,0.00009863196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001077711,0.0001935841,0.001456667,0.003150772,0.0003067098,0.0002750529,0.008038939,0.9743785,0.0005531958,0.000897301,0.004660463,0.005981017],"study_design_scores_gemma":[0.008481612,0.001338134,0.08836231,0.007517435,0.001963257,0.0005681657,0.01019382,0.3202747,0.02254676,0.4743435,0.05150862,0.01290167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09995472,0.002058081,0.8327066,0.002498406,0.002861416,0.001506585,0.0001737047,0.001640964,0.05659948],"genre_scores_gemma":[0.9786761,0.0001287654,0.01980686,0.0001383081,0.0003026257,0.00008919095,0.0000220628,0.0001201551,0.000715916],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8787214,"threshold_uncertainty_score":0.9999191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06314796872352343,"score_gpt":0.3167939015844149,"score_spread":0.2536459328608915,"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."}}