{"id":"W7132913867","doi":"","title":"Shape Memory Polymer Composites for 4D Printing of Wearable Devices","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Materials and Mechanics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"3D printing; Shape-memory polymer; Fabrication; Characterization (materials science); Wearable computer; Wearable technology; Inkwell; Screen printing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002288217,0.0003595995,0.0002466073,0.0009025717,0.0002494263,0.000632752,0.0002030746,0.0004376119,0.005084218],"category_scores_gemma":[0.0002716991,0.0002293628,0.0004244369,0.0006691546,0.0001480289,0.0004248409,0.0003297177,0.0006182489,0.001771949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002913789,"about_ca_system_score_gemma":0.0002366206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001777233,"about_ca_topic_score_gemma":0.0007492083,"domain_scores_codex":[0.9998192,0.00002169668,0.00001199445,0.00003155554,0.0000986617,0.00001678514],"domain_scores_gemma":[0.9999143,0.00003528256,0.00001957008,0.000009250413,0.00001581186,0.000005754437],"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":[0.0000507309,0.00006821031,0.0002385667,0.001623523,0.00002549883,0.0003938586,0.0001921028,0.002223621,0.8291872,0.009510099,0.002066236,0.1544204],"study_design_scores_gemma":[0.000008867682,0.0001851335,0.001038427,0.0001471064,0.00003365056,0.0005800313,0.00006571861,0.002755234,0.8807158,0.001896859,0.1125454,0.0000277658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.2981237,0.2223615,0.2140463,0.00167038,0.001743916,0.0005106713,0.001099408,0.002286539,0.2581576],"genre_scores_gemma":[0.6397508,0.110355,0.1573387,0.0008036207,0.0003386024,0.0004523916,0.000685297,0.0002707915,0.09000488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005084218,"threshold_uncertainty_score":0.01700842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451080774183122,"score_gpt":0.3035031932315976,"score_spread":0.2889923854897664,"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."}}