{"id":"W4389204055","doi":"10.3233/atde44","title":"Advances in Manufacturing Technology XXXVI","year":2023,"lang":"en","type":"book","venue":"Advances in transdisciplinary engineering","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centro para el Desarrollo Tecnológico Industrial; Department of Science and Technology, Ministry of Science and Technology, India; Engineering and Physical Sciences Research Council; China Scholarship Council; Commonwealth Scholarship Commission; Queen's University Belfast; Ministry of Education, India; Queen's University; European Commission; European Regional Development Fund; UK Research and Innovation","keywords":"Computer science; Manufacturing engineering; Engineering","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":[0.0006546333,0.0009977458,0.0008267534,0.002185082,0.0007983879,0.005055231,0.001227779,0.001691318,0.124986],"category_scores_gemma":[0.001459505,0.0005489769,0.0009289383,0.002570463,0.0006891546,0.002616613,0.001545351,0.001990599,0.07115637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001507213,"about_ca_system_score_gemma":0.001286846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001056523,"about_ca_topic_score_gemma":0.001036308,"domain_scores_codex":[0.9988908,0.0001008687,0.00008762224,0.0001639199,0.0006801381,0.00007656452],"domain_scores_gemma":[0.999267,0.0001497124,0.00005117919,0.0001429751,0.0003374678,0.0000516112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007849102,0.00009170046,0.0005650294,0.002023959,0.00005020652,0.000411835,0.0002965567,0.003144694,0.007783049,0.1493048,0.2699724,0.5662773],"study_design_scores_gemma":[0.000003297984,0.00004178199,0.0004081175,0.0003087868,0.00000737887,0.0003073522,0.00006642238,0.0007181683,0.001118715,0.0143815,0.9826258,0.0000126225],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003454536,0.1961852,0.04925818,0.007694312,0.02938775,0.0002147678,0.002013808,0.001755064,0.7100363],"genre_scores_gemma":[0.0454709,0.1434696,0.03623394,0.001948844,0.007291014,0.0002614263,0.003123631,0.0007516729,0.7614491],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.124986,"threshold_uncertainty_score":0.4181199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004560964641833146,"score_gpt":0.2204225595885689,"score_spread":0.2158615949467358,"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."}}