{"id":"W6977346215","doi":"10.6084/m9.figshare.7775543.v1","title":"Additional file 4: 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":"Immigration; Table (database); Government (linguistics); Data collection; Work (physics)","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":[0.001454872,0.001167178,0.0009712494,0.003818504,0.002965554,0.001819179,0.002263189,0.0007372199,0.7274556],"category_scores_gemma":[0.02259825,0.0005702236,0.001028727,0.006699115,0.0004030333,0.001579135,0.0010449,0.0008387176,0.05067414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009817365,"about_ca_system_score_gemma":0.02191601,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8435354,"about_ca_topic_score_gemma":0.908215,"domain_scores_codex":[0.9993937,0.00007929155,0.00007197283,0.00009292993,0.000175109,0.0001869689],"domain_scores_gemma":[0.9882641,0.006041341,0.0004597768,0.0004310506,0.004356181,0.0004475071],"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":[0.00009852051,0.00005525657,0.009631642,0.001311545,0.00002835324,0.00005388613,0.0005453269,0.0003554935,0.00003206886,0.0004365372,0.9741471,0.01330423],"study_design_scores_gemma":[0.002368599,0.0001617524,0.3222208,0.009850132,0.0003254772,0.000314213,0.0158678,0.00375801,0.0007304582,0.004060962,0.6399676,0.0003741854],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.00168796,0.00004522302,0.000217126,0.0002108097,0.00003382887,0.0002692335,0.9939985,0.0001507811,0.003386655],"genre_scores_gemma":[0.07235282,0.0006928174,0.007943247,0.0005984567,0.00007631598,0.007761507,0.8676865,0.0005668416,0.04232156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7274556,"threshold_uncertainty_score":0.3887516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02927303064891482,"score_gpt":0.2722916773545707,"score_spread":0.2430186467056559,"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."}}