{"id":"W2296613547","doi":"10.1016/j.drugpo.2016.02.028","title":"Injecting drugs in tight spaces: HIV, cocaine and collinearity in the Downtown Eastside, Vancouver, Canada","year":2016,"lang":"en","type":"article","venue":"International Journal of Drug Policy","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute on Drug Abuse; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health","keywords":"Harm reduction; Politics; Downtown; Criminology; Unintended consequences; Gentrification; Political economy; Sociology; Political science; Public health; Economic growth; Law; Medicine; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009119096,0.000152535,0.0003047678,0.0005149564,0.00003231323,0.00003850517,0.0003687275,0.00004979889,0.00005132547],"category_scores_gemma":[0.001399732,0.0000875577,0.00005187705,0.0003161171,0.00008180384,0.000222778,0.00007330301,0.0004013995,0.000003836684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009478192,"about_ca_system_score_gemma":0.001605517,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2572578,"about_ca_topic_score_gemma":0.6815318,"domain_scores_codex":[0.9979351,0.0001388141,0.0006409379,0.0001500083,0.000881673,0.0002535146],"domain_scores_gemma":[0.9983582,0.0006579845,0.0003467435,0.0001421413,0.0003516026,0.0001432976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001440133,0.0006926092,0.7584128,0.00007526758,0.0003811506,0.002092452,0.07056335,0.0001607545,0.00269363,0.002762673,0.1095573,0.05116792],"study_design_scores_gemma":[0.04258945,0.0007140209,0.572775,0.005298662,0.0001835286,0.004665449,0.1560987,0.001104982,0.006576086,0.005676676,0.2030947,0.001222753],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9501138,0.0001403293,0.00002457751,0.04546651,0.0006336994,0.0001384319,0.00004509438,0.000005241746,0.003432277],"genre_scores_gemma":[0.9949998,0.000161777,0.0001959691,0.001913756,0.001075916,0.000003147037,0.000002475507,0.00001508881,0.001632066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.424274,"threshold_uncertainty_score":0.7476882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772514414574168,"score_gpt":0.324540654484611,"score_spread":0.3068155103388693,"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."}}