{"id":"W2110268537","doi":"10.5267/j.ccl.2015.3.003","title":"Preparation and characterization of nickel oxide nanoparticles and their application in glucose and methanol sensing","year":2015,"lang":"en","type":"article","venue":"Current Chemistry Letters","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chemistry; Methanol; Nickel; Characterization (materials science); Nanoparticle; Nickel oxide; Oxide; Inorganic chemistry; Nanotechnology; Nuclear chemistry; Combinatorial chemistry; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002026725,0.0002492729,0.000207198,0.0002667959,0.0001851392,0.0002122872,0.0003141279,0.0002864597,0.0004918454],"category_scores_gemma":[0.0004222989,0.0001332227,0.000170885,0.0001845768,0.0001308448,0.0001908592,0.0001414846,0.0001793502,0.0002911768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002143144,"about_ca_system_score_gemma":0.0001723402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000833012,"about_ca_topic_score_gemma":0.001346889,"domain_scores_codex":[0.9998485,0.00001449693,0.00002020025,0.00003896948,0.00005980904,0.00001801586],"domain_scores_gemma":[0.9998791,0.00001797702,0.00001905782,0.00001477327,0.00005402004,0.00001510245],"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":[0.00002691145,0.00001368769,0.0001479268,0.00006292567,0.000002353311,0.00005725821,0.00001845926,0.0000656726,0.9961803,0.00007188901,0.00003401319,0.003318544],"study_design_scores_gemma":[0.000002918394,0.00007448361,0.001060689,0.00000368331,0.000007346076,0.0001495238,0.00001750918,0.0007591491,0.9957435,0.00003781889,0.00213837,0.000004954517],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9300624,0.005359912,0.05555015,0.0002666301,0.0001630755,0.0003544916,0.0005822598,0.0002916486,0.0073695],"genre_scores_gemma":[0.9515239,0.001719442,0.04159885,0.00008749861,0.00002847678,0.0001964154,0.0007206393,0.0000493564,0.004075495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000833012,"threshold_uncertainty_score":0.001656353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009739004603973157,"score_gpt":0.2205482028236202,"score_spread":0.2108091982196471,"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."}}