{"id":"W4408543955","doi":"10.1016/j.mattod.2025.03.002","title":"Temperature-responsive multistable kirigami with reprogrammable multi-shape memory","year":2025,"lang":"en","type":"article","venue":"Materials Today","topic":"Advanced Materials and Mechanics","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Research Chairs; Agency for Science, Technology and Research","keywords":"Materials science; Shape-memory alloy; Computer science; Nanotechnology; Composite material","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":[0.0000626699,0.0002399395,0.0001343802,0.0001310888,0.0001311552,0.0003185843,0.0002960234,0.0002565555,0.001018574],"category_scores_gemma":[0.0002274889,0.0001570858,0.0001656277,0.000129502,0.0002539718,0.0003670974,0.0003492922,0.0004706779,0.0003418107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002028834,"about_ca_system_score_gemma":0.00009468103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001528186,"about_ca_topic_score_gemma":0.0004037455,"domain_scores_codex":[0.9999279,0.000006058061,0.000004108478,0.00001906336,0.00002184654,0.00002113243],"domain_scores_gemma":[0.9999125,0.00001594802,0.00002966415,0.00001774841,0.00001016006,0.00001403688],"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":[0.00004012694,0.00001766411,0.0001833219,0.00006292292,0.000005341953,0.00009448145,0.00006071858,0.001808707,0.9873738,0.002145164,0.0001925157,0.008015284],"study_design_scores_gemma":[0.00000720043,0.00008601746,0.0004645129,0.000004888054,0.000005414749,0.0001473753,0.00002057997,0.01122218,0.9838815,0.0004471492,0.003693537,0.00001976887],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9550487,0.001048513,0.03491869,0.0001216074,0.0001214236,0.00003143444,0.0001180011,0.0006850827,0.007906463],"genre_scores_gemma":[0.9896231,0.0002546624,0.008330395,0.00004650516,0.000007202245,0.00002813191,0.00004047813,0.00003251259,0.001636936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001018574,"threshold_uncertainty_score":0.003407478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005963872598995255,"score_gpt":0.2217085654459821,"score_spread":0.2157446928469868,"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."}}