{"id":"W1491356860","doi":"","title":"Irregular Migrant Workers and Social Security","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"European Law and Migration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social security; Political science; Work (physics); Social work; Labour law; Sociology; Public relations; Law","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":[0.001656915,0.0001383887,0.0001976468,0.001873759,0.003100842,0.003199675,0.0004477277,0.001125457,0.005141023],"category_scores_gemma":[0.005433142,0.00008921311,0.0001732609,0.001575166,0.008478482,0.002008705,0.003019048,0.001225308,0.0001769733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002489854,"about_ca_system_score_gemma":0.002419193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008413515,"about_ca_topic_score_gemma":0.01085537,"domain_scores_codex":[0.9987538,0.0006120027,0.00004800232,0.0000731585,0.0001638653,0.0003492321],"domain_scores_gemma":[0.996784,0.001311381,0.001121889,0.0001106894,0.0001599676,0.0005122269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001224332,0.0002644456,0.2253052,0.0002476965,0.0000319419,0.00195651,0.1807074,0.0003973378,0.0001705394,0.5308738,0.006703091,0.05321968],"study_design_scores_gemma":[0.00004344733,0.0002243077,0.3943991,0.001294822,0.0000348748,0.001324677,0.3850766,0.0006693121,0.0001892121,0.119985,0.09671109,0.00004752848],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.89853,0.006417153,0.0001813224,0.0188513,0.0001290039,0.00002295642,0.00003276706,0.000005525684,0.07582997],"genre_scores_gemma":[0.9959503,0.001589184,0.00004088907,0.0003101504,0.00004679268,0.000009221787,0.000008593388,0.000001427451,0.002043452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008413515,"threshold_uncertainty_score":0.01806521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009753448239058559,"score_gpt":0.2618543645501861,"score_spread":0.2521009163111275,"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."}}