{"id":"W4382797645","doi":"10.1002/adma.202303740","title":"Liquid Crystal Networks Meet Water: It's Complicated!","year":2023,"lang":"en","type":"review","venue":"Advanced Materials","topic":"Advanced Materials and Mechanics","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"European Research Council; Natural Sciences and Engineering Research Council of Canada; Academy of Finland; European Commission","keywords":"Soft robotics; Materials science; Morphing; Adaptability; Robot; Self-healing hydrogels; Robotics; Computer science; Artificial intelligence; Nanotechnology; Ecology","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":[0.0002494915,0.0005325792,0.0005150607,0.0009210272,0.0004133401,0.0011795,0.000538356,0.001083224,0.006106475],"category_scores_gemma":[0.0005239769,0.0002090475,0.0003085239,0.001191315,0.0004628043,0.002160674,0.0007311243,0.001662564,0.003171005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005735535,"about_ca_system_score_gemma":0.0009518621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001114668,"about_ca_topic_score_gemma":0.002452503,"domain_scores_codex":[0.9998361,0.00002095214,0.00001148412,0.00002472847,0.00008487658,0.00002192393],"domain_scores_gemma":[0.9998485,0.00005077946,0.00002318844,0.000006334616,0.00004985945,0.00002130169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003446073,0.00004365822,0.0001554056,0.008798739,0.00005188454,0.0001735787,0.0001512565,0.0003266741,0.005748433,0.0255042,0.07768402,0.8813277],"study_design_scores_gemma":[0.000001828578,0.0000193104,0.0001052288,0.0006969207,0.000009699974,0.0001718417,0.00004730026,0.00005230716,0.0006207711,0.002113498,0.9961557,0.000005661205],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005348446,0.9856989,0.0007651643,0.0026756,0.001186425,0.00001204835,0.00005508489,0.00003671843,0.009035102],"genre_scores_gemma":[0.004021599,0.9847139,0.0007524985,0.001360732,0.0004865075,0.00001674897,0.00007054552,0.00001137367,0.008566044],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006106475,"threshold_uncertainty_score":0.02042818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0404330109918614,"score_gpt":0.3016733704001362,"score_spread":0.2612403594082748,"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."}}