{"id":"W4226334284","doi":"10.21428/cb6ab371.b8df6aab","title":"“Did Not Return in Time for Curfew”: A Descriptive Analysis of Homeless Missing Persons Cases","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Curfew; Missing data; Descriptive statistics; Population; Scholarship; Criminology; Psychology; Social psychology; Political science; Medicine; Sociology; Demography; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002234383,0.0001589284,0.0003272672,0.003399651,0.001408479,0.001396782,0.0009359131,0.0004893137,0.001296541],"category_scores_gemma":[0.00942295,0.0003392085,0.0002854314,0.00318097,0.001285873,0.001196515,0.001478253,0.0007550177,0.000298119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372911,"about_ca_system_score_gemma":0.001551216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02683211,"about_ca_topic_score_gemma":0.03842805,"domain_scores_codex":[0.9983277,0.0004805672,0.0003033405,0.0002036918,0.0003828119,0.0003018376],"domain_scores_gemma":[0.9928135,0.002805107,0.002736271,0.0005032711,0.0007326738,0.0004090314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006508119,0.0001676782,0.9407035,0.00009315108,0.00001761216,0.001128909,0.05155683,0.00006745973,0.0004008994,0.0007590914,0.0008347784,0.004205015],"study_design_scores_gemma":[0.000003243814,0.0001086578,0.8073762,0.0001254157,0.00001290239,0.001715715,0.1876165,0.000340329,0.0003999911,0.0002230177,0.002055078,0.00002295253],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984856,0.00004765695,0.000142172,0.0001072813,0.00000196064,0.00005599842,0.0006953889,0.00000284617,0.0004610708],"genre_scores_gemma":[0.9978654,0.0001871447,0.0002685732,0.00008170882,0.00000483428,0.0001044082,0.001157237,0.000007223054,0.0003233836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02683211,"threshold_uncertainty_score":0.05335182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.123279073659477,"score_gpt":0.4342787287736163,"score_spread":0.3109996551141392,"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."}}