{"id":"W4402893169","doi":"10.1016/j.heliyon.2024.e38484","title":"Digital technology and Chinese-style industrial modernization: Dynamic threshold effect based on R&D Human resources","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Weifang University of Science and Technology; Federation for the Humanities and Social Sciences","keywords":"Modernization theory; Style (visual arts); Engineering; Industrial engineering; Manufacturing engineering; Economics; Geography; Economic growth","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006900214,0.0003687103,0.0003725306,0.001955141,0.0003954847,0.001544954,0.0004481073,0.0003551781,0.005009476],"category_scores_gemma":[0.002123704,0.0001493352,0.0009898159,0.002122953,0.0008162409,0.001269566,0.0009575493,0.0004819229,0.0003375655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001727373,"about_ca_system_score_gemma":0.001952904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02689124,"about_ca_topic_score_gemma":0.01721814,"domain_scores_codex":[0.9994535,0.00007481562,0.00003483819,0.000137177,0.0001323829,0.0001673689],"domain_scores_gemma":[0.9987304,0.0004866301,0.000284092,0.00008858433,0.0001894603,0.0002208855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000150606,0.0001645081,0.8872994,0.0001496807,0.0003819199,0.0005681618,0.0008107718,0.04163007,0.002602758,0.03278206,0.00116753,0.03229258],"study_design_scores_gemma":[0.00003268065,0.0002592332,0.8624185,0.00004696154,0.0003288273,0.0002114528,0.001669097,0.1162784,0.002142522,0.01249789,0.004058975,0.00005557093],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9756464,0.0004577815,0.01130382,0.0004338048,0.00001843856,0.00006466005,0.0005225384,0.00009992097,0.01145252],"genre_scores_gemma":[0.9980578,0.0001453123,0.0004577645,0.00001303968,0.000004923343,0.00001305392,0.0001335891,0.000004052555,0.001170467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02689124,"threshold_uncertainty_score":0.05346942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01654498403992138,"score_gpt":0.2159726004885704,"score_spread":0.199427616448649,"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."}}