{"id":"W6902285382","doi":"10.6084/m9.figshare.7775552.v1","title":"Additional file 5: of Barriers and recruitment strategies for precarious status migrants in Montreal, Canada","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Table (database); Government (linguistics); Work (physics); Race (biology)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001239908,0.001060512,0.001109346,0.003958817,0.00295388,0.001940253,0.00254885,0.0008069318,0.723572],"category_scores_gemma":[0.02054384,0.0006277897,0.001169142,0.007167198,0.0003695069,0.001552619,0.001042038,0.0008199516,0.05511987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01075187,"about_ca_system_score_gemma":0.02003555,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8961074,"about_ca_topic_score_gemma":0.9400773,"domain_scores_codex":[0.9993318,0.0000749981,0.00008450278,0.0001003232,0.0001813991,0.0002269732],"domain_scores_gemma":[0.9884877,0.005227291,0.0005684161,0.0004120529,0.004785055,0.0005194609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000811479,0.00004226882,0.007124017,0.001453653,0.00002671269,0.00003636535,0.0003067052,0.0002700986,0.00002357627,0.0003255079,0.9805619,0.009748098],"study_design_scores_gemma":[0.00254515,0.0001457466,0.2766342,0.0127681,0.000345055,0.0002804074,0.01020527,0.003012824,0.0005542396,0.003105147,0.6900769,0.0003268875],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0006934547,0.00004328228,0.0000999271,0.0001337232,0.00002017158,0.0001518969,0.9964696,0.00009491074,0.002292973],"genre_scores_gemma":[0.04722116,0.0007168015,0.005270698,0.0006986513,0.00006881632,0.004607336,0.8999461,0.0005211645,0.04094936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.723572,"threshold_uncertainty_score":0.3942909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04812396220640756,"score_gpt":0.2772957847436543,"score_spread":0.2291718225372468,"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."}}