{"id":"W7066806523","doi":"","title":"Inclusive Design: To AgeTech or not to AgeTech?","year":2021,"lang":"en","type":"other","venue":"Archive of research processes and output produced by RCA (Royal College of Art)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Appeal; Population; Population ageing; Ethnic group; Universal design; State (computer science); Pension; Affect (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001739177,0.0005374891,0.001164699,0.001791936,0.0002567208,0.000159864,0.003248644,0.0002042892,0.0002776394],"category_scores_gemma":[0.005779332,0.0004424446,0.000122735,0.003287622,0.0003973811,0.00014002,0.004907104,0.000635577,0.00007171851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009322188,"about_ca_system_score_gemma":0.002436804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003727419,"about_ca_topic_score_gemma":0.0007742566,"domain_scores_codex":[0.9933589,0.0005946166,0.0007003531,0.001991654,0.002110589,0.001243913],"domain_scores_gemma":[0.9944791,0.001116954,0.00035933,0.00193539,0.001325399,0.0007838006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004467907,0.0002708002,0.000008852536,0.002389565,0.0002686268,0.0001913044,0.0008334689,0.00002022988,0.006301421,0.0009230718,0.9816591,0.006686776],"study_design_scores_gemma":[0.0006862397,0.002523284,0.00002229877,0.002497445,0.0000497752,0.00001318793,0.0002960249,0.0002773237,0.1460884,0.0006180218,0.8461816,0.0007463412],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0009599141,0.01353509,0.5420551,0.02791783,0.0008775865,0.0248973,0.01366313,0.001035205,0.3750588],"genre_scores_gemma":[0.01268899,0.001352667,0.1636232,0.0005069327,0.0003404875,0.000510686,0.0001608757,0.0003654422,0.8204508],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.445392,"threshold_uncertainty_score":0.9998027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04469881363703455,"score_gpt":0.3513398849090371,"score_spread":0.3066410712720025,"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."}}