{"id":"W4307836026","doi":"10.36548/jtcsst.2022.4.001","title":"A Novel Multimodal Method for Depression Identification","year":2022,"lang":"en","type":"article","venue":"Journal of Trends in Computer Science and Smart Technology","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Modalities; Identification (biology); Depression (economics); Mood; Anxiety; Modality (human–computer interaction); Intervention (counseling); Mental health; Enthusiasm; Psychology; Psychological intervention; Psychiatry; Medicine; Clinical psychology; Computer science; Artificial intelligence; Social 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004102605,0.0007913984,0.0006118611,0.000705339,0.0003217428,0.0006902418,0.0007467772,0.0008845511,0.00442097],"category_scores_gemma":[0.001001353,0.0002007617,0.0009535585,0.0005926052,0.0001980784,0.0005735043,0.0008596216,0.0008767433,0.001485829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003289996,"about_ca_system_score_gemma":0.0005890805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002325675,"about_ca_topic_score_gemma":0.003194174,"domain_scores_codex":[0.9997298,0.00003954956,0.00001673372,0.00009119168,0.00007371172,0.00004894876],"domain_scores_gemma":[0.9998388,0.00003721225,0.00001450229,0.000016868,0.00007749406,0.0000150712],"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":[0.0003604049,0.0001438426,0.00266345,0.0001803262,0.000125382,0.0002622324,0.0001016904,0.01383896,0.05090976,0.002758216,0.01078063,0.9178752],"study_design_scores_gemma":[0.00005516577,0.000299477,0.007484382,0.00008018531,0.000179715,0.000736944,0.0001364387,0.9490504,0.02291789,0.005433605,0.01356509,0.00006081954],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02801193,0.002174286,0.9618385,0.0005520742,0.0004473348,0.0001798775,0.0006812813,0.001351028,0.004763728],"genre_scores_gemma":[0.4396102,0.002601078,0.5288326,0.001136702,0.000518579,0.000621573,0.00227334,0.0002241573,0.02418178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00442097,"threshold_uncertainty_score":0.01478958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04247353679696887,"score_gpt":0.377145317478758,"score_spread":0.3346717806817892,"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."}}