{"id":"W4399388981","doi":"10.1007/s10845-024-02433-z","title":"Development of a mobile 3D printer and comparative evaluation against traditional gantry systems","year":2024,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; UK Research and Innovation; Canadian Institute for Advanced Research","keywords":"Workspace; Robot; Mobile robot; 3D printing; Fidelity; Quality (philosophy); Computer science; 3d printed; Real-time computing; Engineering; Simulation; Artificial intelligence; Mechanical engineering; Manufacturing engineering; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005437366,0.0001661129,0.0002855072,0.0003293723,0.00004287448,0.0000715327,0.0001384077,0.00006909912,0.00004519826],"category_scores_gemma":[0.00001982907,0.0001341881,0.00007345946,0.00004930571,0.00004931806,0.000156008,0.00004404681,0.0003349494,0.000008683957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000179913,"about_ca_system_score_gemma":0.00004866849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.908378e-7,"about_ca_topic_score_gemma":7.353102e-7,"domain_scores_codex":[0.9987211,0.00002702818,0.0006460951,0.0001204204,0.0003380213,0.0001473017],"domain_scores_gemma":[0.999502,0.0001449246,0.0001355121,0.00008850446,0.00008241281,0.00004662958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004617764,0.0001056235,0.00005554948,0.00192388,0.001412407,0.00006621582,0.01005666,0.3563784,0.01452223,0.0006893903,0.001206773,0.6135367],"study_design_scores_gemma":[0.0001221824,0.00005178101,0.0007405609,0.001233413,0.00004678375,0.00009714391,0.001916981,0.03450144,0.946133,0.0001795335,0.01479512,0.0001821012],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718228,0.002899474,0.02319806,0.000009133355,0.0007361442,0.0001763841,0.000006536164,0.0001153335,0.001036163],"genre_scores_gemma":[0.9945027,0.0002109528,0.00512141,0.000002902169,0.0001063342,0.00001552502,0.000004424753,0.00001457581,0.00002120114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9316107,"threshold_uncertainty_score":0.5472034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07613361151141858,"score_gpt":0.2791591177590484,"score_spread":0.2030255062476298,"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."}}