{"id":"W4360989125","doi":"10.18280/ria.370105","title":"Predicting Psychosomatic Disorders Arising from Intensive Exposure to Social Networks - Using Machine Learning Techniques","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Mental Health Research Topics","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Psychology; Artificial intelligence; Computer science","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":[0.0009662754,0.0004097989,0.0003322965,0.002570731,0.0003161914,0.0006963793,0.0002513336,0.0005661155,0.00146578],"category_scores_gemma":[0.005705366,0.0001182473,0.0006986061,0.001127353,0.000184471,0.0006516948,0.0004367776,0.0006108755,0.0002365105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003985716,"about_ca_system_score_gemma":0.0003336892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004949871,"about_ca_topic_score_gemma":0.006819196,"domain_scores_codex":[0.9995597,0.0002198814,0.00004363426,0.00006215616,0.00006655321,0.00004804637],"domain_scores_gemma":[0.9963151,0.002419026,0.0007481478,0.00009864867,0.0002050057,0.0002142056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001348174,0.0001978687,0.9630339,0.00005765803,0.00009814642,0.0001096308,0.000121958,0.006525438,0.0003470677,0.0001546148,0.000315645,0.02890344],"study_design_scores_gemma":[0.00001212503,0.0003084375,0.8650473,0.000060265,0.00009737021,0.0004236901,0.0008068869,0.1303703,0.0005889826,0.001729463,0.0005326883,0.00002236655],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915803,0.0004647516,0.005346271,0.0004355247,0.00002202292,0.00006851282,0.0008973883,0.00003502925,0.001150303],"genre_scores_gemma":[0.9960195,0.0002044607,0.003080577,0.00002618932,0.00002238206,0.00002224998,0.0004410823,0.000002223879,0.0001812047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004949871,"threshold_uncertainty_score":0.009842098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1103709675151744,"score_gpt":0.4152246126643752,"score_spread":0.3048536451492008,"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."}}