{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03929577,0.00123987,0.0008671391,0.00528747,0.004870953,0.01809176,0.003064308,0.003433509,0.006922718],"category_scores_gemma":[0.06181744,0.001150134,0.00160182,0.003529295,0.03192542,0.02806688,0.009946804,0.003417331,0.001103021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003067264,"about_ca_system_score_gemma":0.005848427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001476669,"about_ca_topic_score_gemma":0.0009937306,"domain_scores_codex":[0.9536988,0.03468728,0.001769113,0.003164351,0.005351933,0.00132851],"domain_scores_gemma":[0.8990273,0.0642329,0.00453032,0.02422702,0.006230468,0.001752038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001073257,0.00009143957,0.002911313,0.0004125459,0.00003114076,0.0002825342,0.08088639,0.002912637,0.002788825,0.8206048,0.00148205,0.08748896],"study_design_scores_gemma":[0.0001260376,0.0003886123,0.001979972,0.0008511845,0.0001024669,0.0008122489,0.04460847,0.01170988,0.00782809,0.7325547,0.198903,0.0001353888],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1021711,0.001496029,0.8080397,0.006267788,0.0003562016,0.000521999,0.0000807585,0.0009582483,0.08010819],"genre_scores_gemma":[0.6775779,0.0006559438,0.3129266,0.0005117701,0.00007799311,0.0006469393,0.000125912,0.0003494862,0.007127512],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03929577,"threshold_uncertainty_score":0.2078184,"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."}}