{"id":"W4402852106","doi":"10.1002/adfm.202411975","title":"Autonomous Sensing Architected Materials","year":2024,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Science and Technology, Ministry of Science and Technology, India; European Commission; University of Sydney; University of Guelph","keywords":"Materials science; Nanotechnology; Systems engineering; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002695043,0.0003796467,0.000349063,0.0003369518,0.0002534679,0.0007557545,0.0007644104,0.0007909667,0.001413253],"category_scores_gemma":[0.000614655,0.0003432478,0.0003896655,0.0001745056,0.001252488,0.001127665,0.0005721497,0.0006001233,0.0002563293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005135929,"about_ca_system_score_gemma":0.0005243616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00112413,"about_ca_topic_score_gemma":0.001074005,"domain_scores_codex":[0.9998299,0.00002812317,0.000004704742,0.000044584,0.0000726171,0.00002011619],"domain_scores_gemma":[0.9997836,0.00007570751,0.00003217213,0.00006428964,0.00003034416,0.00001387098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001785453,0.00005071706,0.0006263178,0.0000871181,0.00002031855,0.0001126553,0.00005665467,0.8625734,0.04760983,0.07778789,0.0003788054,0.01067854],"study_design_scores_gemma":[0.000002136074,0.0000161018,0.0001725221,0.000004713706,0.00000292751,0.00002094101,0.000009978375,0.9878085,0.002489986,0.008554754,0.0009107848,0.000006571351],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1926252,0.0006627875,0.7729321,0.0005025309,0.0001330965,0.00009657846,0.0002027075,0.000698177,0.03214683],"genre_scores_gemma":[0.9484488,0.0004263333,0.04750294,0.00008361987,0.00002662664,0.0001100406,0.00007874351,0.00004341544,0.003279281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001413253,"threshold_uncertainty_score":0.00472784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01106205986219405,"score_gpt":0.2106672129601797,"score_spread":0.1996051530979857,"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."}}