{"id":"W2990860118","doi":"10.1007/s11051-019-4716-x","title":"Quantifying the nanoparticles concentration in nano-PCM","year":2019,"lang":"en","type":"article","venue":"Journal of Nanoparticle Research","topic":"Phase Change Materials Research","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Nanoparticle; Sedimentation; Nanofluid; Nano-; Chemical engineering; Particle size; Nanotechnology; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004544533,0.00009351252,0.000213979,0.0002091725,0.00007509727,0.0001755921,0.0004291121,0.00005509573,0.0002413956],"category_scores_gemma":[0.0003064975,0.00006451114,0.00005093104,0.0008147822,0.0001001252,0.0004103306,0.00007470201,0.0004687207,0.0002683842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002151096,"about_ca_system_score_gemma":0.000104816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001779024,"about_ca_topic_score_gemma":0.00002789364,"domain_scores_codex":[0.9973527,0.0004374497,0.0005070444,0.0001081936,0.0009526956,0.0006418952],"domain_scores_gemma":[0.9987819,0.0004927574,0.00005373224,0.0002559905,0.0002903132,0.0001253472],"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":[0.00008817636,0.00005314037,0.007321343,0.00005591675,0.00001533088,0.00003883657,0.0006890869,0.002471985,0.9868663,0.0002411906,0.0004499743,0.001708732],"study_design_scores_gemma":[0.0009016756,0.0001840625,0.005484285,0.0001080142,0.000002906723,0.00004169693,0.0006570352,0.01452487,0.9766043,0.0002405912,0.001168142,0.00008244399],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970983,0.001149118,0.000006343158,0.0007030439,0.0003336567,0.0002882853,0.000001576786,0.00001910294,0.0004005358],"genre_scores_gemma":[0.9994736,0.0002636196,0.0000453927,0.00001417913,0.0001304406,0.00001051807,3.253399e-7,0.00002352149,0.00003838867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01205289,"threshold_uncertainty_score":0.3449625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1717168459972343,"score_gpt":0.3999265596137238,"score_spread":0.2282097136164895,"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."}}