{"id":"W3125572641","doi":"10.1145/3434462","title":"Filtering and Informing the Design Space","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Computer-Human Interaction","topic":"Design Education and Practice","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; University of Melbourne; Aarhus Universitet","keywords":"Space (punctuation); Generative Design; Computer science; Design education; Experience design; Perspective (graphical); Architecture; Human–computer interaction; Engineering design process; Filter (signal processing); Design thinking; Focus (optics); User experience design; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001433493,0.0001377303,0.0000975013,0.00009695243,0.0003208161,0.0002277869,0.0001280802,0.00004954173,0.0003166758],"category_scores_gemma":[0.00001807772,0.0001277791,0.00004717782,0.0001667038,0.00001967546,0.000558629,0.000007022646,0.0003667679,0.00006047286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007533906,"about_ca_system_score_gemma":0.00001790417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001482654,"about_ca_topic_score_gemma":0.00002060828,"domain_scores_codex":[0.9993296,0.00008025182,0.0001850114,0.0001564514,0.0001037314,0.0001449686],"domain_scores_gemma":[0.9989514,0.0005469925,0.00003661499,0.0003569305,0.00005373108,0.00005435104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004414536,0.0001637173,0.00001323397,0.0001047945,0.0002574415,0.0000236343,0.004577903,0.2936512,0.02186561,0.0006065795,0.005725187,0.6729665],"study_design_scores_gemma":[0.001242933,0.0003965248,0.002278953,0.0004180796,0.000211743,0.001738367,0.002988846,0.4475996,0.1610169,0.001643382,0.379345,0.001119649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01782817,0.00004717928,0.9778438,0.0009160441,0.00177497,0.0001159658,0.000001678354,0.0002308727,0.001241374],"genre_scores_gemma":[0.9737409,0.0001114905,0.02500894,0.0003193211,0.0001836789,0.00003297687,0.000005498555,0.00002755355,0.00056966],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9559127,"threshold_uncertainty_score":0.5210679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03992110125466884,"score_gpt":0.2815082266798996,"score_spread":0.2415871254252307,"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."}}