{"id":"W2041499034","doi":"10.1039/b401795c","title":"Sub-micrometre imaging of metal surface corrosion by scanning Kelvin nanoprobe","year":2004,"lang":"en","type":"article","venue":"The Analyst","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanoprobe; Corrosion; Materials science; Kelvin probe force microscope; Metal; Micrometer; Metallurgy; Nanotechnology; Analytical Chemistry (journal); Optics; Chemistry; Atomic force microscopy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001663705,0.0002750811,0.0002474989,0.0002328977,0.0002031343,0.0002348029,0.0004310637,0.0005216959,0.001323003],"category_scores_gemma":[0.0003149552,0.0002308476,0.0001464603,0.0001119056,0.000360093,0.0004222204,0.0003249544,0.0005498145,0.0006964676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002814131,"about_ca_system_score_gemma":0.0001895547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009649787,"about_ca_topic_score_gemma":0.001747941,"domain_scores_codex":[0.9998525,0.00001326357,0.000006623027,0.00002825473,0.00007073906,0.00002859941],"domain_scores_gemma":[0.9997547,0.00009711823,0.00003214314,0.00004416863,0.00005293316,0.00001888913],"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":[0.00001091323,0.000004076625,0.00005538031,0.00002001492,0.000001700113,0.00002633515,0.00001248001,0.0001098376,0.9982432,0.0001496077,0.00005996405,0.001306557],"study_design_scores_gemma":[0.0000100686,0.00009541027,0.004058165,0.000005188155,0.000006590903,0.0004024572,0.00005229766,0.01234536,0.9793815,0.0004247108,0.003204502,0.00001386867],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8276467,0.002394605,0.1615684,0.0003987075,0.00008910704,0.00009573164,0.0006524273,0.001513848,0.005640521],"genre_scores_gemma":[0.8826779,0.0009076445,0.1120383,0.0001436292,0.00001880038,0.0001050602,0.0003199258,0.0001149945,0.003673766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001323003,"threshold_uncertainty_score":0.004425943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005111359821641524,"score_gpt":0.2476640212620242,"score_spread":0.2425526614403827,"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."}}