{"id":"W4407014208","doi":"10.52202/078369-0020","title":"3D-Printing Mechatronics Components for Reconfigurable Robotics","year":2024,"lang":"en","type":"article","venue":"","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Mechatronics; Robotics; Artificial intelligence; Computer science; 3D printing; Robot; Engineering; Control engineering; Manufacturing engineering; Mechanical engineering","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":[0.0001710593,0.0005581205,0.0003843683,0.0007419594,0.0002723958,0.001195043,0.0008565281,0.0008222712,0.00995184],"category_scores_gemma":[0.0003967023,0.0003731247,0.00063272,0.000586117,0.0004884413,0.0007749929,0.0009753871,0.0007635964,0.003696207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004372577,"about_ca_system_score_gemma":0.000255212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003525213,"about_ca_topic_score_gemma":0.0007812886,"domain_scores_codex":[0.999542,0.00002282494,0.00001877401,0.00005460989,0.0003252226,0.00003656473],"domain_scores_gemma":[0.9997556,0.00004930681,0.00004142193,0.00009597596,0.00004282465,0.0000148386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001276447,0.00005970126,0.0004771739,0.0006625653,0.00005550771,0.0004951219,0.0001227079,0.01876917,0.7245436,0.02858669,0.005072798,0.2210273],"study_design_scores_gemma":[0.00002865683,0.0002165399,0.002232397,0.00009593114,0.00005352923,0.001927636,0.00004751155,0.04490351,0.8186449,0.008274172,0.1234821,0.00009298745],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08525354,0.007807815,0.768425,0.0005994412,0.001419537,0.0001701804,0.0007563316,0.006567674,0.1290006],"genre_scores_gemma":[0.6271781,0.00368456,0.317974,0.0004918595,0.0001886469,0.0001133837,0.0007739689,0.0008353502,0.04876014],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00995184,"threshold_uncertainty_score":0.03329217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02608319731682588,"score_gpt":0.2350062549505369,"score_spread":0.2089230576337111,"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."}}