{"id":"W3206952463","doi":"10.2196/17062","title":"User Reviews of Depression App Features: Sentiment Analysis","year":2021,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"mHealth; Psychoeducation; Sentiment analysis; Mental health; Psychology; Population; App store; Internet privacy; Depression (economics); World Wide Web; Medicine; Psychological intervention; Computer science; Psychiatry; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002457073,0.0004930315,0.0004918044,0.004931303,0.0006003687,0.001325032,0.0002373771,0.0003020744,0.001126663],"category_scores_gemma":[0.01509138,0.0001592496,0.0005220536,0.002977083,0.0002793542,0.00114363,0.0008215146,0.0003641093,0.0006809005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006091314,"about_ca_system_score_gemma":0.0005080308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002096657,"about_ca_topic_score_gemma":0.004576307,"domain_scores_codex":[0.996864,0.0008560453,0.0004947432,0.0003727824,0.001269867,0.0001425976],"domain_scores_gemma":[0.9829904,0.009720746,0.002505952,0.0003154653,0.004235957,0.0002314531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001563653,0.0002765882,0.4139595,0.00930909,0.0005904797,0.002030974,0.0329359,0.001026952,0.0466801,0.001237369,0.06244363,0.4279458],"study_design_scores_gemma":[0.00004655321,0.0004570251,0.8531294,0.001165773,0.000500444,0.002111086,0.01425263,0.02407769,0.01287913,0.001030685,0.09016941,0.000180048],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9575593,0.003407593,0.007644796,0.000918521,0.0002596918,0.0008688656,0.01961199,0.0003954174,0.009333803],"genre_scores_gemma":[0.961713,0.001659869,0.01840259,0.0003626031,0.0002963686,0.0009872172,0.01277887,0.0001261257,0.003673452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004931303,"threshold_uncertainty_score":0.01299435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.107851681452572,"score_gpt":0.5387747139067632,"score_spread":0.4309230324541912,"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."}}