{"id":"W6950706067","doi":"10.5683/sp3/3dy2bo","title":"Replication Data and Code for: From engineer to taxi driver? Language proficiency and the occupational skills of immigrants","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Toronto Metropolitan University","funders":"","keywords":"Replication (statistics); Replicate; Immigration; Language proficiency; Code (set theory)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004736832,0.002108126,0.001487291,0.00374754,0.001679395,0.003023579,0.003336939,0.002195056,0.1892185],"category_scores_gemma":[0.03445783,0.001423202,0.002342917,0.007135117,0.0007452861,0.001992099,0.002158616,0.002897538,0.1266257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001906634,"about_ca_system_score_gemma":0.004156548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08097827,"about_ca_topic_score_gemma":0.1221468,"domain_scores_codex":[0.9965678,0.0009017197,0.0005350416,0.001037805,0.0005496022,0.000408025],"domain_scores_gemma":[0.985543,0.004554321,0.00126824,0.004418622,0.003525104,0.0006907801],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007746612,0.00002288004,0.001559202,0.0002582526,0.0000456308,0.00001407691,0.00004479416,0.0001647421,0.00003999897,0.0004439923,0.996106,0.001223016],"study_design_scores_gemma":[0.001181681,0.00004940236,0.01712425,0.0004107987,0.0001501061,0.00008922174,0.000310138,0.000456775,0.0004102836,0.00255028,0.977176,0.00009116866],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002172667,0.00002528013,0.000165206,0.00009946778,0.00005919181,0.00005425548,0.9983302,0.0002287712,0.0008204633],"genre_scores_gemma":[0.001246343,0.00002584007,0.0006885846,0.0001200699,0.00002254316,0.0006758228,0.9943019,0.0002974297,0.002621524],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9952632,"threshold_uncertainty_score":0.6329988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02135881077111352,"score_gpt":0.3130579222952952,"score_spread":0.2916991115241817,"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."}}