{"id":"W7133002358","doi":"","title":"Atmospheric carbonaceous aerosols: sampling, analysis, and characterization","year":2004,"lang":"","type":"dissertation","venue":"TSpace","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; University of Toronto; Canadian Foundation for Climate and Atmospheric Sciences; Government of Canada","keywords":"Aerosol; Sorption; Vaporization; Carbon fibers; Sorbent; Particulates; Particle (ecology); Total organic carbon; Analytical Chemistry (journal)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005457953,0.0004430649,0.0005176446,0.0008932984,0.0007215418,0.000556864,0.0007488696,0.000426293,0.000381124],"category_scores_gemma":[0.0004069611,0.0001769227,0.000152443,0.0008334225,0.0002557001,0.0001863444,0.0003324201,0.0003218069,0.0002554569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000899422,"about_ca_system_score_gemma":0.00123378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03021093,"about_ca_topic_score_gemma":0.06290482,"domain_scores_codex":[0.9989401,0.00005029993,0.00004115867,0.0002164159,0.0006837018,0.00006841899],"domain_scores_gemma":[0.9998171,0.00001848333,0.00002088842,0.00001502905,0.000106517,0.00002207713],"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":[0.0001681122,0.0001342731,0.05994765,0.0004600456,0.00004918871,0.0001303973,0.0001662285,0.001088486,0.8941088,0.0002231692,0.0006905925,0.04283305],"study_design_scores_gemma":[0.00004388122,0.0004223042,0.3627951,0.00004934753,0.00007935625,0.0006741899,0.0001472839,0.01135377,0.6070523,0.0002331656,0.01710562,0.00004368314],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.920672,0.003620867,0.05957269,0.00009999947,0.00004424372,0.001328883,0.006317239,0.0006945935,0.007649587],"genre_scores_gemma":[0.8465509,0.004504083,0.1331211,0.0002113955,0.00008006264,0.001055889,0.008546649,0.0001275259,0.005802436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03021093,"threshold_uncertainty_score":0.06007022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01414360105120546,"score_gpt":0.2692245953746844,"score_spread":0.255080994323479,"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."}}