{"id":"W3005328510","doi":"10.22215/etd/2017-11926","title":"Collectively Intelligent Material Systems: Compositing Digital Systems Within Architectural Smart Material Applications","year":2017,"lang":"en","type":"dissertation","venue":"","topic":"Architecture and Computational Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Smart material; Architecture; Field (mathematics); Process (computing); Systems engineering; Engineering; Architectural engineering; Compositing; Architectural pattern; Computer science; Facade; Software engineering; Artificial intelligence; Civil engineering; Nanotechnology; Software","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001075029,0.0005341281,0.0005874194,0.0002473777,0.0004190095,0.001522511,0.0004842472,0.000282993,0.00004252253],"category_scores_gemma":[0.0000117179,0.0004992672,0.0001295362,0.00009558214,0.00004048395,0.000148926,0.00003062947,0.0003066972,0.0001239059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001830505,"about_ca_system_score_gemma":0.0001080334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001936036,"about_ca_topic_score_gemma":0.00004483046,"domain_scores_codex":[0.9980589,0.00004990436,0.0007247503,0.0004242866,0.0003846324,0.0003575169],"domain_scores_gemma":[0.9989861,0.00009384601,0.0002853373,0.0003587428,0.0001492768,0.0001266871],"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":[0.001013821,0.0001300517,0.00005822606,0.006888413,0.001948611,0.00007297851,0.00465637,0.9241114,0.02160605,0.01128165,0.004371819,0.02386056],"study_design_scores_gemma":[0.003215857,0.001227408,0.003802422,0.008354248,0.001551392,0.002447903,0.01084879,0.7436435,0.1203244,0.008237364,0.08255391,0.01379276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4401476,0.001007763,0.2246061,0.00002114736,0.0316287,0.008816256,0.003686252,0.003509503,0.2865767],"genre_scores_gemma":[0.9835994,0.000005343997,0.0003590793,0.000004233577,0.001364342,0.0008659661,0.005885858,0.0001426985,0.007773031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5434518,"threshold_uncertainty_score":0.9997459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009189874753311112,"score_gpt":0.2230130776456218,"score_spread":0.2138232028923107,"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."}}