{"id":"W3165252799","doi":"10.3233/shti210338","title":"The Potential of an Artificial Intelligence for Disability Advocacy: The WikiDisability Project","year":2021,"lang":"en","type":"book-chapter","venue":"Studies in health technology and informatics","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's and Gender Studies et Recherches Féministes; Centre for Disability Prevention and Rehabilitation; Canadian Centre on Disability Studies; York University","funders":"","keywords":"Computer science; Assistive technology; Human rights; Artificial intelligence; World Wide Web; Internet privacy; Data science; Human–computer interaction; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003040564,0.0004378318,0.0002212128,0.002244546,0.001671246,0.00646594,0.0009589682,0.001475257,0.008556248],"category_scores_gemma":[0.003707987,0.0001746724,0.0002940177,0.002361553,0.002203438,0.009412941,0.003887415,0.001574951,0.002100519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001240031,"about_ca_system_score_gemma":0.002732745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002541202,"about_ca_topic_score_gemma":0.003865627,"domain_scores_codex":[0.9991853,0.0004211823,0.00004706597,0.00007933832,0.0002248374,0.00004222617],"domain_scores_gemma":[0.9968858,0.00236167,0.00006164237,0.0002263473,0.0001942708,0.0002701082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002980471,0.0001016364,0.0007447852,0.0006380049,0.00001680675,0.000307498,0.005897821,0.001093112,0.001039149,0.4421707,0.1740248,0.3739359],"study_design_scores_gemma":[0.000005198622,0.00001125691,0.0003280094,0.0002161364,0.000004088036,0.0002416314,0.001328264,0.0008335766,0.0006472981,0.03701336,0.9593614,0.000009912424],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02803996,0.02870914,0.111937,0.03228285,0.003918173,0.0002910593,0.001626057,0.002703187,0.7904926],"genre_scores_gemma":[0.1648065,0.03001038,0.3166241,0.003823614,0.0007868909,0.0005774272,0.006493698,0.001888792,0.4749886],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008556248,"threshold_uncertainty_score":0.02862352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09041029031807536,"score_gpt":0.4393571431567855,"score_spread":0.3489468528387101,"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."}}