{"id":"W4360765147","doi":"10.1109/asonam55673.2022.10068572","title":"A Time-Dependent-Based Approach to Enhance Self-Harm Prediction","year":2022,"lang":"en","type":"article","venue":"","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université Laval","funders":"","keywords":"Harm; Computer science; Artificial intelligence; Machine learning; Natural language processing; Data mining; Psychology; 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":[0.001685443,0.0007549332,0.0007380437,0.002629706,0.0004078792,0.0006606697,0.0009241628,0.0009808172,0.002131052],"category_scores_gemma":[0.006679455,0.000228777,0.0007847149,0.001558333,0.0002966899,0.001037988,0.0007102764,0.0014755,0.001433639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003657071,"about_ca_system_score_gemma":0.0006474038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003175494,"about_ca_topic_score_gemma":0.006022871,"domain_scores_codex":[0.999124,0.0002581397,0.00006997368,0.0002628222,0.0002100425,0.00007504832],"domain_scores_gemma":[0.9952561,0.002577282,0.000554907,0.0004899298,0.0009326397,0.000189057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00138547,0.00332093,0.1233308,0.0003269129,0.0005643403,0.0005003301,0.0004015185,0.07968844,0.03924737,0.004356463,0.007344617,0.7395328],"study_design_scores_gemma":[0.00001932669,0.0005019773,0.02607519,0.00002163269,0.00009522725,0.0002113273,0.00006309595,0.9622729,0.004742153,0.003677155,0.002265686,0.00005432813],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2675338,0.0009611134,0.7216427,0.000927316,0.00028296,0.0003632256,0.001874361,0.002503457,0.003911143],"genre_scores_gemma":[0.8179615,0.0002772014,0.175565,0.0002138348,0.00027429,0.0002497196,0.001589147,0.0001023328,0.003767078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003175494,"threshold_uncertainty_score":0.008913577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02033827030279314,"score_gpt":0.2954162459384664,"score_spread":0.2750779756356733,"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."}}