{"id":"W3037049230","doi":"10.1080/23311916.2020.1771818","title":"Evaluation of the influence parameters of Industry 4.0 and their impact on the Quebec manufacturing SMEs: The first findings","year":2020,"lang":"en","type":"article","venue":"Cogent Engineering","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Context (archaeology); Globalization; Digital transformation; Business; Manufacturing; Competition (biology); Industrial organization; Marketing; Industry 4.0; Economic shortage; The Internet; Business model; Engineering; Computer science; Economics; Market economy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001568221,0.0003113048,0.0002764917,0.001130395,0.001026573,0.001420212,0.0003498755,0.0003432679,0.003958935],"category_scores_gemma":[0.005782957,0.00009765532,0.0003039261,0.001205949,0.0008793892,0.0005745807,0.0008349371,0.0003579214,0.0002616731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007509749,"about_ca_system_score_gemma":0.004754277,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5602913,"about_ca_topic_score_gemma":0.6415635,"domain_scores_codex":[0.9987119,0.0004361848,0.00004883098,0.0001132682,0.0004331352,0.0002567122],"domain_scores_gemma":[0.991939,0.003405211,0.0007770325,0.0001995107,0.002875556,0.0008036494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005948402,0.0006543997,0.8962725,0.0002741422,0.00008104903,0.001277858,0.0196817,0.001600311,0.007696361,0.00120307,0.001143837,0.06951975],"study_design_scores_gemma":[0.000006495427,0.0004887742,0.9692481,0.00004955006,0.00004174245,0.00006418262,0.02447432,0.001333554,0.001660763,0.00006334938,0.002546208,0.00002293831],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946342,0.00008160712,0.00007743631,0.00007636981,0.000002410785,0.00002640894,0.00006917517,0.000006806682,0.005025728],"genre_scores_gemma":[0.9981942,0.00006603457,0.00008367549,0.00001586991,0.000001824664,0.0000132919,0.00004948332,0.000001640679,0.001574015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4397087,"threshold_uncertainty_score":0.8845963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0278716299392373,"score_gpt":0.2215610973196509,"score_spread":0.1936894673804136,"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."}}