{"id":"W2051858267","doi":"10.1039/b509724j","title":"Scanning Kelvin nanoprobe detection in materials science and biochemical analysis","year":2005,"lang":"en","type":"article","venue":"The Analyst","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanoprobe; Kelvin probe force microscope; Biomolecule; Work function; Nanotechnology; Adsorption; Substrate (aquarium); Desorption; Materials science; Molecule; Chemistry; Atomic force microscopy; Nanoparticle; Physical chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008218663,0.0001045809,0.0001628977,0.0002449982,0.0001476484,0.00005534965,0.0001768989,0.00006764678,0.00000224317],"category_scores_gemma":[0.00009004012,0.00007186839,0.00005775413,0.001217073,0.0003312332,0.000007580219,0.0001172326,0.0000562504,0.000001015432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003581569,"about_ca_system_score_gemma":0.00002366437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009115868,"about_ca_topic_score_gemma":0.0003587542,"domain_scores_codex":[0.9990635,0.00004615421,0.0001948905,0.0003335865,0.0001658819,0.0001959864],"domain_scores_gemma":[0.9994576,0.000006952997,0.00007837187,0.0003165532,0.00009987631,0.00004067028],"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":[0.00001782088,0.0000123099,0.0005287727,0.000001481625,0.00006472416,4.433893e-7,0.00001554963,0.0000326733,0.9952379,0.000008698688,0.00002134308,0.004058234],"study_design_scores_gemma":[0.00007383862,0.00002666122,0.002532793,0.000004160858,0.0001608527,0.000005935564,0.00004881607,0.001013759,0.995342,0.0000230715,0.0006632773,0.000104883],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980828,0.0002093352,0.001237281,0.0002665349,0.000009622438,0.00005710629,0.000003379547,0.00001531771,0.000118594],"genre_scores_gemma":[0.9982924,0.00008526991,0.001264289,0.000169878,0.00009485806,0.000004889213,0.00001317276,0.000005709768,0.00006945803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003953351,"threshold_uncertainty_score":0.2930708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006228704212004368,"score_gpt":0.2628844070943722,"score_spread":0.2566557028823678,"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."}}