{"id":"W4200524990","doi":"10.32920/16811473","title":"Corporeality: a haptic space","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; Society for the Study of Architecture in Canada","funders":"","keywords":"Haptic technology; Perception; Space (punctuation); Haptic perception; Sight; Architecture; Psychology; Cognitive science; Communication; Computer science; Human–computer interaction; Cognitive psychology; Artificial intelligence; Visual arts; Art; 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":[],"consensus_categories":[],"category_scores_codex":[0.00003759433,0.0001411062,0.0001612689,0.0000421003,0.00001412282,0.00004957868,0.0001049383,0.0001064884,0.0001802491],"category_scores_gemma":[0.000005707529,0.000138497,0.00008021043,0.00004733727,0.00001045023,0.00001206826,0.0001321683,0.0003017449,0.00003510576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002933585,"about_ca_system_score_gemma":0.00004837396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003390757,"about_ca_topic_score_gemma":0.00002622791,"domain_scores_codex":[0.9994818,0.00001490844,0.0001131564,0.0001603572,0.0001223084,0.0001074706],"domain_scores_gemma":[0.9996571,0.00004114522,0.00001409244,0.0002116861,0.0000289862,0.00004699382],"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":[0.000001364113,0.000008476759,0.00002844994,0.0002248886,0.0001328721,0.00005711337,0.0002575352,0.979294,0.000222348,0.005609114,0.005576731,0.008587129],"study_design_scores_gemma":[0.000120421,0.0000123388,0.002202271,0.0001528399,0.00005842696,0.00003790961,0.00005668071,0.9115195,0.0009025005,0.07885326,0.00548247,0.0006013621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01084327,0.0005135924,0.8997167,0.0001845262,0.0004521193,0.0001065394,0.000006057902,0.0005083277,0.08766881],"genre_scores_gemma":[0.9733967,0.00003443883,0.02545807,0.0001178848,0.0001417031,0.00002060122,0.0001094683,0.00002927902,0.0006919093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9625534,"threshold_uncertainty_score":0.5647743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01555353415467765,"score_gpt":0.2106080113917079,"score_spread":0.1950544772370303,"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."}}