{"id":"W2017219794","doi":"10.1063/1.3514138","title":"A total internal reflection fluorescence microscopy study of mass diffusion enhancement in water-based alumina nanofluids","year":2010,"lang":"en","type":"article","venue":"Journal of Applied Physics","topic":"Nanofluid Flow and Heat Transfer","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Rhodamine 6G; Thermal diffusivity; Nanofluid; Total internal reflection fluorescence microscope; Diffusion; Analytical Chemistry (journal); Chemistry; Mass diffusivity; Microscopy; Dispersion (optics); Nanoparticle; Materials science; Fluorescence; Optics; Nanotechnology; Thermodynamics; Chromatography; Physics","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":[0.0002582383,0.0003974707,0.0002780241,0.0002229095,0.0002006731,0.0002030173,0.0003059807,0.0003794728,0.0003838968],"category_scores_gemma":[0.0002826141,0.0001690101,0.0002045414,0.0001399206,0.0003709951,0.0003572107,0.0001693898,0.0004184301,0.0001878055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003059089,"about_ca_system_score_gemma":0.0001469861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000809182,"about_ca_topic_score_gemma":0.0003940942,"domain_scores_codex":[0.9998957,0.00001714006,0.000006221991,0.00003194377,0.00002583537,0.00002316407],"domain_scores_gemma":[0.999811,0.00007917826,0.00004547076,0.00001061436,0.00003933587,0.00001441168],"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":[0.00001659053,0.000004156517,0.00003279112,0.00001384341,8.845263e-7,0.00002314535,0.00002147383,0.00004726855,0.9994813,0.00004127257,0.000005893231,0.0003115496],"study_design_scores_gemma":[0.000007325897,0.0001503702,0.0006612687,0.000003355675,0.000005248981,0.00007389417,0.00002377424,0.001644494,0.9971449,0.00002126626,0.0002564673,0.000007576561],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993018,0.000593175,0.005409234,0.00005701894,0.000009586711,0.00001928423,0.00006867153,0.00008093799,0.0007441117],"genre_scores_gemma":[0.9893094,0.0004517423,0.009286471,0.00002529886,0.00001054419,0.00002559878,0.00006114729,0.00001701411,0.0008127827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000809182,"threshold_uncertainty_score":0.002219498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007104448863446787,"score_gpt":0.234767092769965,"score_spread":0.2276626439065182,"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."}}