{"id":"W3202758585","doi":"10.1080/1331677x.2021.1980731","title":"Enterprise digital transformation and production efficiency: mechanism analysis and empirical research","year":2021,"lang":"en","type":"article","venue":"Economic Research-Ekonomska Istraživanja","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":207,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Science and Technology Commission of Shanghai Municipality","keywords":"Mechanism (biology); Transformation (genetics); Digital transformation; Production (economics); Business; Computer science; Process management; Industrial organization; Economics; Microeconomics; Epistemology; World Wide Web; Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.001428773,0.0001970863,0.0002923431,0.0008655055,0.0002944633,0.0009875097,0.0002044626,0.0001813699,0.0001357843],"category_scores_gemma":[0.0001333157,0.0002213874,0.00009115439,0.0008482879,0.0004007925,0.001600108,0.00008894528,0.0007687917,0.0001458521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003771249,"about_ca_system_score_gemma":0.0001684011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000137462,"about_ca_topic_score_gemma":0.00004923873,"domain_scores_codex":[0.9977944,0.0001283168,0.0005325734,0.0005095622,0.0003918575,0.0006432523],"domain_scores_gemma":[0.9988889,0.0002731525,0.00002599869,0.0004023198,0.0001698253,0.0002398314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007271323,0.001904517,0.04186725,0.004527917,0.007221912,0.0003917626,0.09504506,0.08934166,0.01663056,0.19552,0.0354912,0.511331],"study_design_scores_gemma":[0.006087966,0.001212489,0.04486438,0.0005604136,0.00053367,0.0010478,0.08455905,0.3902214,0.2364995,0.1331699,0.096525,0.004718513],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9554021,0.0001895402,0.002305043,0.001130513,0.0002620418,0.0003555756,0.00009238316,0.0001451127,0.04011771],"genre_scores_gemma":[0.9984761,0.0004338227,0.0001052787,0.000007177113,0.0001254534,0.00001626836,0.00008963069,0.00003212982,0.0007140714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5066125,"threshold_uncertainty_score":0.9522579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08136218540899698,"score_gpt":0.3599189608030482,"score_spread":0.2785567753940513,"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."}}