{"id":"W4366159852","doi":"10.1016/j.matchemphys.2023.127791","title":"Eco-friendly phyllanthus emblica-based ionic polymer composite for enhanced mechanical, electrical, and wearable sensing performance","year":2023,"lang":"en","type":"article","venue":"Materials Chemistry and Physics","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; Ministry of Science, ICT and Future Planning; National Research Foundation of Korea; Ministry of Education","keywords":"Materials science; Wearable computer; Environmentally friendly; Polyvinyl alcohol; Composite number; Ionic bonding; Composite material; Nanotechnology; Computer science; Chemistry; Embedded system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009410083,0.0002089276,0.0003054042,0.000009812003,0.0001890825,0.0001135147,0.00005926952,0.00009337375,0.00002139524],"category_scores_gemma":[0.00001466206,0.0002136294,0.00002748253,0.0001276591,0.00004147206,0.00008623879,0.000026093,0.00005649417,0.000008249978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001554645,"about_ca_system_score_gemma":0.00001049598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003737677,"about_ca_topic_score_gemma":1.328357e-7,"domain_scores_codex":[0.9991055,0.00001362733,0.0002139909,0.0002413236,0.00007493448,0.0003506637],"domain_scores_gemma":[0.9995956,0.00009679355,0.00004785601,0.0001537828,0.00002595489,0.00007995016],"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":[0.000049857,0.000007193963,9.130754e-7,0.0004975625,0.00001680457,0.000001361507,0.00002128014,0.004682365,0.9914986,0.00002825045,0.00005359378,0.003142255],"study_design_scores_gemma":[0.000432235,0.00002927642,0.00001589996,0.00008397293,0.00001995259,0.000006067611,0.000007575968,0.02451382,0.9742125,0.0001696116,0.000252083,0.0002569628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951695,0.00006875502,0.003805851,0.00001498431,0.0001657499,0.00009263453,0.00006599999,0.0003797789,0.0002367156],"genre_scores_gemma":[0.9979348,0.0001875325,0.001237652,0.00002485649,0.0002838045,0.00001925704,0.000104085,0.0000472516,0.0001608161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01983146,"threshold_uncertainty_score":0.8711554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009086801762162556,"score_gpt":0.2145225461957093,"score_spread":0.2054357444335467,"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."}}