{"id":"W4411258466","doi":"10.1007/s00181-025-02775-4","title":"Spatial Nexus: Natural Resources and Economic Growth","year":2025,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Natural Resources and Economic Development","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Nexus (standard); Natural resource; Economic geography; Spatial econometrics; Natural (archaeology); Economics; Natural resource economics; Regional science; Geography; Econometrics; Computer science; Political science","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":[0.0006240119,0.0003065051,0.0003755343,0.001130017,0.0003671658,0.002360888,0.0003679694,0.0006555392,0.01068804],"category_scores_gemma":[0.00488337,0.0001503472,0.0002717708,0.003865886,0.001574284,0.003906892,0.001202093,0.0006521931,0.0003975631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001280619,"about_ca_system_score_gemma":0.001777805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02551739,"about_ca_topic_score_gemma":0.02750193,"domain_scores_codex":[0.9997649,0.0001164334,0.00001568138,0.00003950141,0.00003799633,0.00002551656],"domain_scores_gemma":[0.995735,0.002702943,0.0007865684,0.0001472951,0.0003299363,0.0002981662],"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":[0.0001213,0.00008874513,0.1333562,0.0003746443,0.0001857993,0.0004173393,0.0003807071,0.03313762,0.0002068282,0.7729373,0.01464652,0.04414714],"study_design_scores_gemma":[0.00002345549,0.00002893625,0.04266058,0.0002550888,0.0001267823,0.0002317976,0.002123374,0.02493406,0.0003222915,0.9029478,0.02632352,0.00002234017],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6609955,0.06793604,0.05819984,0.09040798,0.0008117618,0.00005314906,0.005123926,0.0002709218,0.1162008],"genre_scores_gemma":[0.982998,0.008998251,0.001659098,0.0002594064,0.0001962583,0.00001482413,0.0002880654,0.00001545784,0.005570666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02551739,"threshold_uncertainty_score":0.05073774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843352891510666,"score_gpt":0.2344912836716413,"score_spread":0.2160577547565347,"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."}}