{"id":"W2800315451","doi":"10.52842/conf.caadria.2010.259","title":"ROBO studio: towards architectronics","year":2010,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Computer-Aided Architectural Design Research in Asia","topic":"Architecture and Computational Design","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Architecture; Mechatronics; Framing (construction); Computer science; Studio; Systems engineering; Applications architecture; Systems architecture; Engineering; Architectural engineering; Human–computer interaction; Artificial intelligence","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":[0.001290255,0.0003197215,0.0003141879,0.0007223851,0.0001484477,0.0001895295,0.00228848,0.0001003354,0.00005409497],"category_scores_gemma":[0.0001599062,0.0002396224,0.0001520267,0.0006679317,0.0003249769,0.0001661965,0.0004615614,0.002192285,0.00002348603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001417016,"about_ca_system_score_gemma":0.0001832711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003286987,"about_ca_topic_score_gemma":0.00003591346,"domain_scores_codex":[0.996851,0.0000763978,0.0005128992,0.000456985,0.001468227,0.0006345376],"domain_scores_gemma":[0.9985043,0.0004646321,0.00009911245,0.0002326742,0.0005626038,0.0001366725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005028162,0.0002571578,0.0006935624,0.0001811126,0.0002609798,0.0000210734,0.001403877,0.1571834,0.2629035,0.2996153,0.002017644,0.2749595],"study_design_scores_gemma":[0.0008843949,0.0005137383,0.01092454,0.0004316487,0.000008511163,0.0001765352,0.00007388502,0.654541,0.06875175,0.2624421,0.0007578525,0.0004939854],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9300607,0.00003892407,0.02432328,0.007573368,0.001611211,0.00133671,0.000021839,0.0002631873,0.03477079],"genre_scores_gemma":[0.974104,0.00002126265,0.02524893,0.00006480027,0.0003369857,0.0000926367,0.000003705583,0.00004056827,0.00008709079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4973576,"threshold_uncertainty_score":0.977152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0808996126400793,"score_gpt":0.3222059941146154,"score_spread":0.2413063814745361,"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."}}