{"id":"W2154581575","doi":"10.1021/la8037704","title":"Pinning, Retraction, and Terracing of Evaporating Droplets Containing Nanoparticles","year":2009,"lang":"en","type":"article","venue":"Langmuir","topic":"Nanomaterials and Printing Technologies","field":"Engineering","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Engineering and Physical Sciences Research Council","keywords":"Nanoparticle; Chemical engineering; Materials science; Nanotechnology; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001149842,0.00006293695,0.0001137263,0.00003996033,0.00004099907,0.00002251601,0.00004577836,0.00005472822,0.000007033782],"category_scores_gemma":[0.00003629834,0.00005930255,0.00001150553,0.00006422782,0.00001675154,0.00007847605,0.00001375653,0.00005784361,0.000001523266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005842289,"about_ca_system_score_gemma":0.000001850352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001361228,"about_ca_topic_score_gemma":0.000001991102,"domain_scores_codex":[0.9996211,0.00000700729,0.0001470313,0.00006860834,0.00004590476,0.0001103789],"domain_scores_gemma":[0.9998504,0.00001520787,0.00003233102,0.00007667166,0.00001319616,0.00001217572],"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":[0.000003970007,0.000004167887,0.003372151,0.00003830724,0.000007134974,0.00000360399,0.0003739024,0.0001981926,0.9747239,0.0008846123,0.0001455272,0.02024457],"study_design_scores_gemma":[0.0002001073,0.00008949076,0.07885697,0.00009885748,0.000009732199,0.00001862447,0.0002725696,0.004135356,0.9138066,0.00134101,0.001010833,0.0001598442],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982132,0.0002979331,0.0002053078,0.0001102454,0.00005828094,0.00003460184,0.0000010678,0.0004341202,0.0006452519],"genre_scores_gemma":[0.9976695,0.00001485795,0.002246693,0.0000203594,0.00003283619,0.000001463515,0.000001180529,0.000007304101,0.000005835478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07548482,"threshold_uncertainty_score":0.2418288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008551342676779062,"score_gpt":0.211750341419775,"score_spread":0.2031989987429959,"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."}}