{"id":"W811993811","doi":"10.3762/bjnano.6.150","title":"Improved atomic force microscopy cantilever performance by partial reflective coating","year":2015,"lang":"en","type":"article","venue":"Beilstein Journal of Nanotechnology","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Cantilever; Atomic force microscopy; Materials science; Kelvin probe force microscope; Coating; Atomic force acoustic microscopy; Microscopy; Non-contact atomic force microscopy; Nanotechnology; Conductive atomic force microscopy; Piezoresponse force microscopy; Photoconductive atomic force microscopy; Magnetic force microscope; Composite material; Optics; Optoelectronics; Scanning capacitance microscopy; Physics; Scanning electron microscope; Scanning confocal electron 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002677133,0.0001792682,0.000322206,0.0001210134,0.0001146921,0.0000282851,0.000394589,0.0001480323,0.00002783671],"category_scores_gemma":[0.00001463183,0.0001619729,0.0001046709,0.0002399511,0.0001547509,0.0001740333,0.00008975893,0.000435739,0.00001051653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001015953,"about_ca_system_score_gemma":0.0002194468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007716222,"about_ca_topic_score_gemma":0.000001500078,"domain_scores_codex":[0.9988159,0.0000292542,0.0005059786,0.0001872203,0.0001174257,0.0003442367],"domain_scores_gemma":[0.9988017,0.00002440607,0.0005770571,0.0002468762,0.0002426865,0.0001072441],"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":[0.00007188074,0.00007816259,0.002820034,0.00000551096,0.00004761642,9.705772e-7,0.0001393645,0.0000152228,0.9774171,0.001665259,0.004239154,0.01349975],"study_design_scores_gemma":[0.0009093648,0.000470357,0.00001974642,0.00004062546,0.00003172694,0.00003477998,0.0001863963,0.000624494,0.9846915,0.001847354,0.01097014,0.0001735036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.942246,0.0002317588,0.0563232,0.0003564519,0.0001427608,0.0001895912,0.00002378923,0.00005211804,0.0004343896],"genre_scores_gemma":[0.986912,0.00001403173,0.01246363,0.00005711807,0.0001313314,0.0000230349,0.000008017559,0.00002654503,0.0003642845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04466606,"threshold_uncertainty_score":0.6605064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118543248829546,"score_gpt":0.2845643797464427,"score_spread":0.2733789472581472,"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."}}