{"id":"W4402054155","doi":"10.3390/ijerph21091150","title":"QuickPic AAC: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking","year":2024,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Human–computer interaction; Psychology","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":[0.003626712,0.00007914702,0.000195687,0.0004477361,0.0002465647,0.00004157053,0.0004409619,0.00009962518,0.0001942802],"category_scores_gemma":[0.0002374359,0.00007109776,0.00004379745,0.0001530224,0.0001447089,0.0002566497,0.0001224311,0.0006050999,0.0000138184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000968803,"about_ca_system_score_gemma":0.0005283458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009983861,"about_ca_topic_score_gemma":0.0003329594,"domain_scores_codex":[0.9978622,0.0004543892,0.0006122377,0.0002119473,0.0005432388,0.0003159544],"domain_scores_gemma":[0.9985849,0.0005601319,0.0002133582,0.0002116162,0.0001935305,0.0002364661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001339248,0.004184771,0.4557403,0.000743434,0.0002161596,0.00002642478,0.0101453,0.0001195664,0.09016097,0.02788195,0.02047844,0.3889635],"study_design_scores_gemma":[0.003303705,0.003075713,0.4401513,0.001222797,0.000008830741,0.00002028688,0.01450178,0.0250145,0.001408487,0.001677704,0.5092992,0.0003156838],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9311877,0.000865868,0.01603709,0.05048435,0.0001953238,0.0008171312,0.0001895693,0.00001270352,0.0002102586],"genre_scores_gemma":[0.9965515,0.0005447239,0.001405474,0.0008234534,0.0002597854,0.00009825078,0.00006556964,0.00001192499,0.0002393347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4888208,"threshold_uncertainty_score":0.2899283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2143984261217091,"score_gpt":0.504510690454369,"score_spread":0.2901122643326599,"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."}}