{"id":"W4291155385","doi":"10.3390/su14169922","title":"Digital Inclusive Finance, Human Capital and Inclusive Green Development—Evidence from China","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Promotion (chess); Inclusive development; Human capital; Inclusive growth; China; Digitization; Capability approach; Inclusion (mineral); Business; Economic growth; Economics; Political science; Computer science; Sociology; Social science; Poverty","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000719619,0.0003002906,0.0005197806,0.0001982603,0.001045226,0.0001146529,0.0005599647,0.00008774979,0.0006664621],"category_scores_gemma":[0.0004091938,0.0004039891,0.0001032698,0.0002143533,0.0002978589,0.0008598054,0.002910161,0.0003648738,0.00005346486],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003880192,"about_ca_system_score_gemma":0.0001973105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002828697,"about_ca_topic_score_gemma":0.0001875938,"domain_scores_codex":[0.9974087,0.00005294132,0.0008223046,0.001108929,0.00009073861,0.0005163539],"domain_scores_gemma":[0.9985409,0.0001259893,0.0004983995,0.0006676256,0.00003994814,0.000127123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004873169,0.000264521,0.9184636,0.00006751344,0.00008215387,0.00003907741,0.009691074,0.0006520294,0.00001266235,0.06492686,0.0001730681,0.005578638],"study_design_scores_gemma":[0.0005083861,0.0001085056,0.6758724,0.000005356409,0.000004934119,0.00000395086,0.001521056,0.0001490571,0.0000547499,0.2960806,0.02522485,0.0004662453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918942,0.001195943,0.0002363987,0.001470898,0.0001503699,0.0004923182,0.0003712566,0.0000512817,0.004137358],"genre_scores_gemma":[0.9965057,0.00003245662,0.0002324568,0.0001110704,0.00008285305,0.0002066524,0.0001149294,0.00003984657,0.002674071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2425913,"threshold_uncertainty_score":0.9999437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009411233607954025,"score_gpt":0.214334300974854,"score_spread":0.2049230673668999,"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."}}