{"id":"W4298759487","doi":"10.52842/conf.ecaade.2006.014","title":"Architectural Design Spaces and Interpersonal Communication-Changes in Design Vocabulary and Language Expression","year":2006,"lang":"en","type":"article","venue":"eCAADe proceedings","topic":"Design Education and Practice","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Intertek (Canada)","funders":"","keywords":"Computer science; Human–computer interaction; Engineering design process; Context (archaeology); Design language; Gesture; Vocabulary; Domain (mathematical analysis); Expression (computer science); Software; Process (computing); Design studio; Interaction design; Design process; Software engineering; Multimedia; Programming language; Studio; Artificial intelligence; Engineering; Work in process; Linguistics","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":[0.0002875824,0.0001137568,0.00009851449,0.0001226458,0.00005357921,0.0001168101,0.00008531241,0.0000537677,0.00002624719],"category_scores_gemma":[0.00004923221,0.0001091551,0.000007489878,0.0001056295,0.00004272967,0.0002417591,0.0000299268,0.0001805602,0.000004201431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002295684,"about_ca_system_score_gemma":0.000006919013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005594973,"about_ca_topic_score_gemma":0.00002250547,"domain_scores_codex":[0.9995228,0.00002687661,0.0001021421,0.0001279634,0.00007658485,0.0001436228],"domain_scores_gemma":[0.9996659,0.0001870844,0.00003121261,0.00005405797,0.00001730563,0.00004449475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002514041,0.0001254611,0.01290726,0.0005100573,0.00003975465,0.00001294682,0.09516603,0.001570903,0.8192051,0.001037114,0.02990971,0.03926424],"study_design_scores_gemma":[0.003476558,0.000416417,0.1337168,0.001567909,0.000106635,0.0007878797,0.03709123,0.1677064,0.6262675,0.007495313,0.019034,0.002333365],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797009,0.00542085,0.009540629,0.001980839,0.00006326841,0.0003322615,0.000001542831,0.0002055115,0.002754262],"genre_scores_gemma":[0.969925,0.000141119,0.02957633,0.00007181737,0.00005008483,0.00003894299,0.000002901505,0.00001904121,0.0001747167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1929376,"threshold_uncertainty_score":0.4451214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01357430284164487,"score_gpt":0.2318418476272448,"score_spread":0.2182675447855999,"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."}}