{"id":"W3036830449","doi":"10.22215/sdhlab/kt/2019.7","title":"Infographic: Substance Use in Rural Youth.","year":2020,"lang":"en","type":"report","venue":"","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Infographic; Substance use; Geography; Advertising; Psychology; Computer science; Business; Data mining; Psychiatry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004397365,0.0005088887,0.0002797078,0.002678034,0.0005360697,0.0006216718,0.000640512,0.0004057534,0.03325881],"category_scores_gemma":[0.001405447,0.0002934028,0.0003594531,0.002546048,0.00009874436,0.0005254889,0.001126544,0.0005051495,0.007560253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001039456,"about_ca_system_score_gemma":0.003493775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3129487,"about_ca_topic_score_gemma":0.4580722,"domain_scores_codex":[0.9998072,0.00002006931,0.00002173013,0.00001547441,0.00008206505,0.00005345006],"domain_scores_gemma":[0.9981126,0.0001383537,0.0002399973,0.00004708005,0.0007322025,0.0007297421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002595653,0.0002919907,0.1107352,0.0007195976,0.00002630716,0.0001320253,0.000184522,0.0001362946,0.0002589759,0.0001712497,0.8318724,0.0552118],"study_design_scores_gemma":[0.000127023,0.0001596273,0.8754348,0.0005145912,0.00004906736,0.0001425692,0.0005801794,0.0002108984,0.0003145931,0.0001035384,0.1223451,0.00001805387],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.02042043,0.000913781,0.0001285841,0.001529057,0.0003312947,0.0004243814,0.9555275,0.0003315312,0.02039331],"genre_scores_gemma":[0.0772846,0.004925239,0.001048437,0.001390304,0.0007641732,0.001472175,0.8387053,0.0001602342,0.07424958],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3129487,"threshold_uncertainty_score":0.6222544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4415438362278479,"score_gpt":0.4886984891141991,"score_spread":0.04715465288635118,"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."}}