{"id":"W3022033914","doi":"10.3386/w27075","title":"Immigration, Innovation, and Growth","year":2020,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Western University","funders":"","keywords":"Immigration; Economic geography; Political science; Economics; Law","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":[0.0006142122,0.0002085378,0.0002436625,0.001121532,0.0005848207,0.001002176,0.0002217887,0.0005342634,0.006451531],"category_scores_gemma":[0.005921577,0.00009303639,0.0006723425,0.001779836,0.0008552134,0.0006796243,0.001098801,0.000684951,0.0003555435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007148393,"about_ca_system_score_gemma":0.0009198691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01873804,"about_ca_topic_score_gemma":0.0175359,"domain_scores_codex":[0.9996542,0.0001293107,0.00001658313,0.00006838666,0.00004305613,0.00008853597],"domain_scores_gemma":[0.9942468,0.00334599,0.001568181,0.0002008004,0.0002884296,0.0003498433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001144274,0.0002015997,0.8535163,0.0001674617,0.0002023008,0.0005671236,0.0008299489,0.02360121,0.000677072,0.08254425,0.004260257,0.03331809],"study_design_scores_gemma":[0.00006110578,0.0002289369,0.8194282,0.0002132492,0.0003171346,0.0004862093,0.00216904,0.05156281,0.001489808,0.1068553,0.0171335,0.00005475648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973585,0.00196737,0.004306057,0.003874537,0.00005732139,0.00001166692,0.0009070876,0.00005731953,0.01523365],"genre_scores_gemma":[0.9967977,0.0007382974,0.0006032308,0.00008523525,0.0000336608,0.000009856613,0.0002143145,0.000004950472,0.001512767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01873804,"threshold_uncertainty_score":0.03725791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.288426944428529,"score_gpt":0.4134343001258064,"score_spread":0.1250073556972774,"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."}}