{"id":"W4293730684","doi":"10.3390/machines10090742","title":"Smart Manufacturing—Theories, Methods, and Applications","year":2022,"lang":"en","type":"article","venue":"Machines","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Measure (data warehouse); Smart manufacturing; Computer science; Manufacturing engineering; Engineering; Data mining","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":[0.002258859,0.001090315,0.001009284,0.002995085,0.0009591298,0.004787561,0.001760143,0.002625997,0.006475114],"category_scores_gemma":[0.003254084,0.0007082013,0.0008001439,0.003401474,0.007786336,0.005940968,0.00221957,0.003073479,0.002132358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001830553,"about_ca_system_score_gemma":0.00164639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001449724,"about_ca_topic_score_gemma":0.0009809844,"domain_scores_codex":[0.99857,0.0004927058,0.0001017729,0.0002084796,0.0005529485,0.00007415307],"domain_scores_gemma":[0.9982479,0.001092811,0.0001126884,0.0002743991,0.0002101369,0.00006205701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008223967,0.00002718467,0.0002287356,0.0003765174,0.0000139627,0.00004487828,0.0002075274,0.00325584,0.000274787,0.9408585,0.004130279,0.05057352],"study_design_scores_gemma":[0.000007502375,0.00002166397,0.0002285858,0.0003770198,0.000007562631,0.0001104589,0.0002206269,0.01086457,0.0005193375,0.9089612,0.07865879,0.00002276899],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.006193604,0.1775108,0.6307252,0.01444266,0.001336261,0.0001701711,0.0002772259,0.0006317624,0.1687123],"genre_scores_gemma":[0.3374012,0.1944016,0.4209973,0.003099578,0.002941318,0.000765148,0.0004563164,0.0003046371,0.03963295],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.006475114,"threshold_uncertainty_score":0.02166146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01014435829958817,"score_gpt":0.2609161380977357,"score_spread":0.2507717797981476,"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."}}