{"id":"W4403576082","doi":"10.1145/3643834.3661626","title":"\"I'm not alone in that battle\": Designing Mobile AR for Mental Health Communication and Community Connectedness","year":2024,"lang":"en","type":"article","venue":"Designing Interactive Systems Conference","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Social connectedness; Computer science; Mental health; Context (archaeology); Public health; Human–computer interaction; Visualization; Field (mathematics); Data visualization; Data science; Psychology; Medicine; Social psychology; Artificial intelligence; Nursing","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":[0.003844094,0.001016895,0.000250768,0.0006935893,0.001607237,0.002817502,0.00103406,0.001580771,0.003854141],"category_scores_gemma":[0.01328631,0.0004667922,0.0006142972,0.0002490494,0.001421379,0.002321428,0.002698535,0.0008141568,0.0006717251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004021506,"about_ca_system_score_gemma":0.0008178553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00102371,"about_ca_topic_score_gemma":0.001913562,"domain_scores_codex":[0.9972579,0.002152885,0.00007747261,0.0001548807,0.0001640582,0.0001926728],"domain_scores_gemma":[0.9946752,0.00415526,0.0002616005,0.0002137973,0.0003718919,0.0003223915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001509564,0.001376718,0.03073358,0.004132878,0.0002258853,0.005499907,0.3637759,0.01726818,0.1000333,0.03062712,0.02373838,0.4210785],"study_design_scores_gemma":[0.00119671,0.009129839,0.04251708,0.004020225,0.001190551,0.00894306,0.2884175,0.1720654,0.05360255,0.04833953,0.3695704,0.001007169],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.640354,0.0009691978,0.3209763,0.005906634,0.000356561,0.001195778,0.0001708534,0.002466057,0.02760453],"genre_scores_gemma":[0.8428132,0.0003587813,0.1511707,0.0004570934,0.00004163232,0.0007718242,0.00006494123,0.0001564152,0.004165532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003854141,"threshold_uncertainty_score":0.02032977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08635694404742629,"score_gpt":0.3429844013873901,"score_spread":0.2566274573399638,"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."}}