{"id":"W3192085897","doi":"10.2196/19824","title":"Deep Learning With Anaphora Resolution for the Detection of Tweeters With Depression: Algorithm Development and Validation Study","year":2021,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Mental Health via Writing","field":"Psychology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; King's College London; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; Comunidad de Madrid","keywords":"Computer science; Mental health; Social media; Set (abstract data type); Artificial intelligence; Machine learning; Resolution (logic); Depression (economics); Publication; Natural language processing; Information retrieval; World Wide Web; Psychology; Psychiatry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004816253,0.001635077,0.001402695,0.001319742,0.0007631094,0.001226214,0.002559814,0.002625537,0.002394904],"category_scores_gemma":[0.008518597,0.0004982786,0.0009838664,0.001184221,0.0004936946,0.001256239,0.001381836,0.002764902,0.0008808891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001601505,"about_ca_system_score_gemma":0.002715627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01862278,"about_ca_topic_score_gemma":0.01317909,"domain_scores_codex":[0.9988673,0.0004010379,0.0001339592,0.0002423788,0.0001906443,0.0001647945],"domain_scores_gemma":[0.9961269,0.002449778,0.0001833274,0.0002143366,0.0009143227,0.0001112946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009542651,0.001588486,0.02397256,0.0004288905,0.0005492087,0.0003677469,0.000168093,0.4195126,0.002985379,0.001632037,0.01053345,0.5373074],"study_design_scores_gemma":[0.00004180599,0.00007949356,0.0007548587,0.00002135565,0.00003393304,0.00002878166,0.00004164178,0.9973553,0.0007785917,0.0004862119,0.000371981,0.000006005529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5098029,0.01017657,0.4561296,0.003767802,0.0005095705,0.001271527,0.001800388,0.008571055,0.007970591],"genre_scores_gemma":[0.7942158,0.001370319,0.1955523,0.0007992681,0.0000940973,0.0008634199,0.003174538,0.0001297055,0.003800543],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01862278,"threshold_uncertainty_score":0.03702879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03192610461197318,"score_gpt":0.3688892145672306,"score_spread":0.3369631099552574,"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."}}