{"id":"W2406844049","doi":"10.1038/srep26293","title":"Removal of electrostatic artifacts in magnetic force microscopy by controlled magnetization of the tip: application to superparamagnetic nanoparticles","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Superparamagnetism; Magnetic force microscope; Magnetization; Magnetic field; Magnetic nanoparticles; Materials science; Nanomaterials; Characterization (materials science); Nanoparticle; Nanotechnology; Microscopy; Electrostatics; Nuclear magnetic resonance; Chemistry; Physics; Optics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003780314,0.0004201324,0.000298729,0.0002672745,0.0002213721,0.0002284293,0.0005297781,0.0008113087,0.0003996672],"category_scores_gemma":[0.0006927862,0.0001890897,0.0001952298,0.0001662618,0.0004329424,0.0003404333,0.0003284565,0.0003927658,0.0001389107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000198536,"about_ca_system_score_gemma":0.0001453588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002887094,"about_ca_topic_score_gemma":0.0003779181,"domain_scores_codex":[0.9997774,0.00003370969,0.00001074197,0.00005171513,0.0001014281,0.00002505751],"domain_scores_gemma":[0.9996674,0.0001367993,0.00008084912,0.00004335047,0.00005368119,0.00001798637],"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":[0.00001515922,0.000011582,0.00007749844,0.00005651681,0.000002415242,0.00005355402,0.00001977104,0.0001870542,0.9947953,0.0001804385,0.00002426026,0.004576542],"study_design_scores_gemma":[0.00001033232,0.0001001546,0.0005914799,0.000005383321,0.000005318219,0.0002167926,0.00001013691,0.008972591,0.9888238,0.0001352084,0.00111721,0.00001145782],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7883836,0.002884472,0.2067064,0.0003043313,0.0001205465,0.0001224592,0.00007387681,0.0003191509,0.001085104],"genre_scores_gemma":[0.8661041,0.001066101,0.1316415,0.000102223,0.00005043592,0.0001004761,0.00006469422,0.00004307213,0.0008274295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008113087,"threshold_uncertainty_score":0.001999199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002788857882609649,"score_gpt":0.234117812668897,"score_spread":0.2313289547862873,"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."}}