{"id":"W6894295061","doi":"10.5683/sp3/0votgb","title":"Replication Data and Code for: Immigrants’ net direct fiscal contribution: How does it change over their lifetime?","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Qualitative Comparative Analysis Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Engineers Without Borders Canada","funders":"","keywords":"Replication (statistics); Code (set theory); Replicate; Net (polyhedron); Data file; Table (database)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00678225,0.001878122,0.001312873,0.004333909,0.002056675,0.002825155,0.003248921,0.002463364,0.2716846],"category_scores_gemma":[0.05806633,0.001570558,0.001969325,0.007554077,0.0008164548,0.001964281,0.002673628,0.003153775,0.1089825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002649169,"about_ca_system_score_gemma":0.006630316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05903495,"about_ca_topic_score_gemma":0.09306203,"domain_scores_codex":[0.9962203,0.001033281,0.0007759706,0.0007988781,0.0007128438,0.0004588433],"domain_scores_gemma":[0.9746935,0.009609975,0.001771484,0.005401094,0.00769741,0.0008265463],"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":[0.00006540393,0.00002379637,0.0009521709,0.0004522302,0.00002164126,0.00001159754,0.00009581017,0.0001022329,0.00003808965,0.0007677144,0.9957402,0.00172913],"study_design_scores_gemma":[0.001348404,0.00003462887,0.01255619,0.000873186,0.00007839249,0.00004580786,0.0005837345,0.0003136633,0.0003367434,0.003633855,0.9801064,0.00008904695],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001911428,0.00001476672,0.0002303231,0.0001219379,0.00005656182,0.0001882844,0.9979449,0.0002033642,0.001048772],"genre_scores_gemma":[0.001953766,0.0000404109,0.002342241,0.0001870717,0.00002409412,0.006761272,0.9836821,0.0004592321,0.00454972],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2716846,"threshold_uncertainty_score":0.9088757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1615619961478336,"score_gpt":0.4451739110805216,"score_spread":0.283611914932688,"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."}}