{"id":"W4392606195","doi":"10.31355/115","title":"Streamlining Denmark’s Immigration Process","year":2024,"lang":"en","type":"article","venue":"Journal of Digital Innovation for Humanity","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Immigration; Process (computing); Computer science; Political science; Process management; Business; Law; Operating system","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":[0.00961222,0.0003644233,0.0002509919,0.001432044,0.008381218,0.01027658,0.001355684,0.001978654,0.007653522],"category_scores_gemma":[0.01190548,0.0003480892,0.0004640257,0.001008752,0.003013777,0.002992267,0.009837846,0.002280925,0.002619913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007317584,"about_ca_system_score_gemma":0.02077052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03807676,"about_ca_topic_score_gemma":0.0367233,"domain_scores_codex":[0.994381,0.002658408,0.0003879371,0.0006208865,0.0009286287,0.001023117],"domain_scores_gemma":[0.9935954,0.00262428,0.0004794466,0.0005767968,0.0009609526,0.001763092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000582499,0.000537415,0.05760548,0.00139981,0.00005799517,0.00409142,0.2383189,0.006843857,0.007964232,0.21585,0.06328629,0.4034621],"study_design_scores_gemma":[0.00003459798,0.0001538041,0.02253115,0.000790789,0.00002387487,0.0004017197,0.1251802,0.003904464,0.002193533,0.01116076,0.8335218,0.0001034016],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5853298,0.00249907,0.03082322,0.02845417,0.001757254,0.0009344582,0.0005695708,0.0007782993,0.3488542],"genre_scores_gemma":[0.8957916,0.001512263,0.01739128,0.002152811,0.0001354146,0.000193462,0.0004280283,0.0001740939,0.08222103],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03807676,"threshold_uncertainty_score":0.07571024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04548824762436733,"score_gpt":0.368348072935666,"score_spread":0.3228598253112986,"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."}}