{"id":"W3089218841","doi":"10.1039/d0ay01017k","title":"Probing arsenic trioxide (ATO) treated leukemia cell elasticities using atomic force microscopy","year":2020,"lang":"en","type":"article","venue":"Analytical Methods","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Toronto; Toronto Public Health; Mount Sinai Hospital; National Research Council Canada; University of Ottawa","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Arsenic trioxide; Arsenic; Atomic force microscopy; Indentation; Chemistry; Nanoindentation; Nanotechnology; Materials science; Biophysics; Composite material; Metallurgy; Biology","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":[0.0001449794,0.0002279785,0.0001226618,0.0003455761,0.0002456417,0.0001678255,0.0001720407,0.0003959704,0.0009632683],"category_scores_gemma":[0.0001992549,0.0001317982,0.0001258021,0.0002610641,0.000198433,0.0002674298,0.0001853037,0.0003005012,0.0001767573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001815572,"about_ca_system_score_gemma":0.0001002599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000907554,"about_ca_topic_score_gemma":0.001784695,"domain_scores_codex":[0.9998672,0.00001501181,0.000008736323,0.00003118369,0.00005750686,0.00002040045],"domain_scores_gemma":[0.9998796,0.00003879714,0.00003126227,0.00001097352,0.00002990712,0.000009492319],"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":[0.00001138147,0.000005075492,0.0001918208,0.00001253425,0.000001364646,0.00001696261,0.00001684255,0.0000783839,0.998675,0.00002286762,0.00001712188,0.0009505478],"study_design_scores_gemma":[0.000004152023,0.0001366691,0.01443105,0.000005600901,0.000009333345,0.0001480062,0.0001044329,0.004491519,0.9783264,0.0001157411,0.002214679,0.00001237347],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842367,0.001060801,0.01205843,0.0001741355,0.00004253739,0.00002964043,0.0004835844,0.0001078585,0.001806243],"genre_scores_gemma":[0.9819741,0.001234057,0.01379193,0.00007448382,0.00001666967,0.00007043692,0.000312747,0.00001885046,0.002506677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009632683,"threshold_uncertainty_score":0.003222466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03925194325849092,"score_gpt":0.3755447129128941,"score_spread":0.3362927696544032,"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."}}