{"id":"W4378087038","doi":"10.3390/polym15112424","title":"Silver Nanoparticle-Embedded Conductive Hydrogels for Electrochemical Sensing of Hydroquinone","year":2023,"lang":"en","type":"article","venue":"Polymers","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"China Scholarship Council","keywords":"Materials science; Self-healing hydrogels; Hydroquinone; Carboxymethyl cellulose; Chemical engineering; Polypyrrole; Anode; Nanoparticle; Electrochemistry; Electrode; Inorganic chemistry; Polymer; Polymer chemistry; Nanotechnology; Sodium; Chemistry; Polymerization; Organic chemistry; Composite material; Physical chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001317002,0.0004294677,0.0001975254,0.0001914289,0.00007803561,0.0001955579,0.0003012668,0.0003999986,0.0005195361],"category_scores_gemma":[0.0001583291,0.0001949774,0.0002126271,0.0001058658,0.0001210294,0.0003026688,0.0002007437,0.0003457745,0.0002644503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001568102,"about_ca_system_score_gemma":0.00009684158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001431362,"about_ca_topic_score_gemma":0.0003828087,"domain_scores_codex":[0.9998809,0.00001460207,0.00001033623,0.00002950691,0.00004662319,0.00001793756],"domain_scores_gemma":[0.9999002,0.00002377441,0.00003159338,0.000006985184,0.00002344447,0.00001394502],"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":[0.000007318856,0.00000512017,0.00001528465,0.0000390832,0.000001770402,0.00002079388,0.000005456789,0.00003229816,0.9989464,0.00001951697,0.00001136737,0.0008956371],"study_design_scores_gemma":[0.000005110618,0.00006971886,0.0001907247,0.000003465795,0.000007197627,0.00009968705,0.000005727345,0.001097382,0.9977981,0.00002460195,0.0006937907,0.000004559062],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9139706,0.00768357,0.07493114,0.0002949559,0.0002227113,0.00008737158,0.0002475376,0.0004998366,0.002062268],"genre_scores_gemma":[0.9654143,0.00213624,0.03012066,0.0001003158,0.00003786772,0.00004107971,0.0001322871,0.00003667949,0.001980503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005195361,"threshold_uncertainty_score":0.001738071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151751716261032,"score_gpt":0.2289957168633258,"score_spread":0.2174781997007155,"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."}}