{"id":"W2338186794","doi":"10.1117/12.2222093","title":"Characterization of origami shape memory metamaterials (SMMM) made of bio-polymer blends","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Materials and Mechanics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Yükseköğretim Kurulu; Council for Higher Education; Ministry of Education, Libya","keywords":"Materials science; Shape-memory polymer; Metamaterial; Shape-memory alloy; Characterization (materials science); Fabrication; Molding (decorative); Polymer; Viscoelasticity; Nanotechnology; Composite material; Optoelectronics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004095736,0.0003334173,0.000649036,0.0001255915,0.00003047234,0.00003089397,0.0006455378,0.0002146582,0.00009288693],"category_scores_gemma":[0.000193908,0.0002449088,0.000432406,0.0002332762,0.0001540562,0.0005921134,0.0001238343,0.000103161,0.000001526775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009000686,"about_ca_system_score_gemma":0.00002466609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002687262,"about_ca_topic_score_gemma":3.800211e-8,"domain_scores_codex":[0.9978539,2.44218e-8,0.001013501,0.0002792169,0.0005011453,0.0003522361],"domain_scores_gemma":[0.9982883,0.00007772773,0.0005025432,0.00007840647,0.0009590257,0.0000939473],"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":[0.00007207987,0.00004592079,0.00001411251,0.0009476938,0.000319603,3.051738e-8,0.0001051765,0.00003916597,0.8385221,0.1591776,0.0001096816,0.0006467298],"study_design_scores_gemma":[0.0007061537,0.0001533194,0.0001360144,0.0004417339,0.0001361903,0.000005046314,0.0001756119,0.003593381,0.9928973,0.0006286567,0.0008708167,0.0002558026],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973475,0.00008846808,0.0002746274,0.0003348517,0.0006809237,0.0003918578,0.0002682405,0.000110815,0.0005027521],"genre_scores_gemma":[0.978396,0.0005413512,0.02004794,0.00002069482,0.0004222103,0.0001166864,0.00001688226,0.0001184616,0.000319784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.158549,"threshold_uncertainty_score":0.9987092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01016040932505245,"score_gpt":0.213758492895677,"score_spread":0.2035980835706246,"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."}}