{"id":"W3209025936","doi":"10.32920/ryerson.14647413.v1","title":"Moody architecture: emotionally intelligent prostheses","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Architecture and Computational Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Architecture; Cybernetics; Phenomenology (philosophy); Doctrine; Computer science; Normative; Cognitive science; Cognitive architecture; Human–computer interaction; Cognition; Psychology; Artificial intelligence; Epistemology; Law; Neuroscience","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"],"consensus_categories":[],"category_scores_codex":[0.00007144004,0.0003117617,0.0002645382,0.0001213518,0.00003422745,0.0001146389,0.0002700208,0.0001813077,0.0004546228],"category_scores_gemma":[0.0000202012,0.0002839009,0.0001900255,0.0001001654,0.00002698458,0.00002209583,0.0002715014,0.0006648703,0.00006158988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000567538,"about_ca_system_score_gemma":0.0001112227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008577726,"about_ca_topic_score_gemma":0.00002260812,"domain_scores_codex":[0.998825,0.00004004882,0.0002773477,0.000333887,0.000306644,0.000217148],"domain_scores_gemma":[0.9993965,0.00009564737,0.00002858631,0.0003113986,0.00008150144,0.00008636553],"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":[0.000003162683,0.00002363758,0.00002146155,0.0001907133,0.0001510612,0.00002079897,0.0006126256,0.9456083,0.0002011271,0.0006083017,0.0007626938,0.05179611],"study_design_scores_gemma":[0.0005675515,0.0002026367,0.01499138,0.001621441,0.0002804773,0.0004153377,0.0005237915,0.5765838,0.03903155,0.3336702,0.02760257,0.004509226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02193068,0.00139621,0.9570714,0.0003825368,0.0006842013,0.0003446496,0.00001561279,0.0006957229,0.01747905],"genre_scores_gemma":[0.956508,0.00009960333,0.04185217,0.0002428964,0.0003478688,0.00008190674,0.0002835016,0.00006897152,0.0005150848],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9345773,"threshold_uncertainty_score":0.9999613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376782497571472,"score_gpt":0.2147230560561823,"score_spread":0.2009552310804676,"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."}}