{"id":"W6921267530","doi":"10.6084/m9.figshare.7775510","title":"Additional file 1: of Barriers and recruitment strategies for precarious status migrants in Montreal, Canada","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Immigration; Government (linguistics); 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":[0.001095564,0.00116903,0.001043447,0.004641749,0.002802857,0.001799568,0.002308576,0.0006346606,0.6872993],"category_scores_gemma":[0.01870742,0.0005816593,0.0008867242,0.008796242,0.0004427297,0.001490501,0.001074971,0.0008157479,0.05525504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009647082,"about_ca_system_score_gemma":0.01964903,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8873386,"about_ca_topic_score_gemma":0.9319995,"domain_scores_codex":[0.999476,0.00005426205,0.00006302136,0.00009305678,0.000159416,0.0001542261],"domain_scores_gemma":[0.9892096,0.004713785,0.0004713267,0.0004077952,0.004780025,0.0004174483],"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":[0.00006563758,0.00003989078,0.01061585,0.0008684929,0.00002243093,0.00004017429,0.0004122301,0.0002451826,0.00003175618,0.0003760712,0.9770706,0.01021175],"study_design_scores_gemma":[0.00124051,0.0001165127,0.3867241,0.005550941,0.0002277922,0.0003451243,0.01034337,0.002486807,0.0006924295,0.002972973,0.5889549,0.0003446027],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001344751,0.00003124032,0.0001235702,0.0001122609,0.00002159724,0.0001158655,0.9959537,0.0001152766,0.002181697],"genre_scores_gemma":[0.04472649,0.0004866333,0.004178545,0.0003037158,0.00004797359,0.003124385,0.9161656,0.0004521983,0.03051435],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6872993,"threshold_uncertainty_score":0.4460297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03002991976183611,"score_gpt":0.2719198912592894,"score_spread":0.2418899714974533,"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."}}