{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006001561,0.0007815482,0.0008038289,0.0003382923,0.0002488025,0.0005496649,0.0009628921,0.001134946,0.001149058],"category_scores_gemma":[0.00157487,0.0006388403,0.0004208234,0.0003030667,0.0003503202,0.0005988602,0.0004940524,0.0007909284,0.0006668876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003273701,"about_ca_system_score_gemma":0.000240165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008906171,"about_ca_topic_score_gemma":0.001320797,"domain_scores_codex":[0.9992061,0.00006015507,0.00005536224,0.0002188657,0.0003447387,0.0001148118],"domain_scores_gemma":[0.9987327,0.0003815168,0.0001824899,0.0002032192,0.0004221178,0.00007791293],"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":[0.00001335243,0.00000497325,0.00007380603,0.00002775031,0.000003867074,0.00001863558,0.00001475695,0.00006233206,0.9986528,0.00001965743,0.00003468978,0.001073432],"study_design_scores_gemma":[0.00001212889,0.0002172626,0.002744239,0.000009575895,0.00002226726,0.0002185331,0.00001505411,0.003966987,0.9914287,0.00002527252,0.001318337,0.00002171098],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9483793,0.00247297,0.04567821,0.0002137898,0.000111933,0.00006730379,0.0002546538,0.0009735855,0.001848071],"genre_scores_gemma":[0.9099833,0.001099246,0.08597042,0.0001485037,0.0000250492,0.00007454172,0.0003763445,0.0001925387,0.002130105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001149058,"threshold_uncertainty_score":0.003843963,"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."}}