{"id":"W2024791377","doi":"10.1016/j.atmosenv.2012.12.025","title":"Cluster analysis of roadside ultrafine particle size distributions","year":2012,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Ministry of Environment; Ontario Innovation Trust","keywords":"Cluster (spacecraft); Ultrafine particle; Particle-size distribution; Particle size; Environmental science; Cluster size; Particle (ecology); Physics; Materials science; Computer science; Nanotechnology; Geology; Chemical engineering; Engineering","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":[0.0003105448,0.0002469801,0.0004015369,0.001833153,0.0008395927,0.0006253663,0.000392455,0.0002330759,0.001565387],"category_scores_gemma":[0.0009143928,0.0001211304,0.0006171677,0.001582289,0.0002092525,0.0002228802,0.000433906,0.000258814,0.000439321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005056934,"about_ca_system_score_gemma":0.0004773676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0177927,"about_ca_topic_score_gemma":0.01840534,"domain_scores_codex":[0.9997106,0.00002832005,0.00001209545,0.00009619431,0.00007909522,0.00007361637],"domain_scores_gemma":[0.9994723,0.0001336561,0.0000488642,0.0000606613,0.000238774,0.00004580248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002894663,0.0006110842,0.3102464,0.0004764801,0.0009720674,0.0005875428,0.00296304,0.08054219,0.3574971,0.004478893,0.008528598,0.2302019],"study_design_scores_gemma":[0.00003038913,0.0002239004,0.6612156,0.00001640073,0.0002177441,0.0003507701,0.001614187,0.2736684,0.05312702,0.002316289,0.007113609,0.0001055795],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760398,0.000105631,0.02030258,0.00003361064,0.00001672711,0.0000389519,0.001694502,0.0003301268,0.001438015],"genre_scores_gemma":[0.9858471,0.00006398134,0.009843648,0.000008154346,0.000009949096,0.00003507497,0.002845397,0.00007905578,0.001267628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0177927,"threshold_uncertainty_score":0.03537828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690284192158326,"score_gpt":0.2610900731681693,"score_spread":0.2441872312465861,"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."}}