{"id":"W2035674272","doi":"10.1021/es035177i","title":"Receptor Modeling of Toronto PM<sub>2.5</sub> Characterized by Aerosol Laser Ablation Mass Spectrometry","year":2004,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Health Canada; University of Toronto","keywords":"Aerosol; Mass spectrometry; Particulates; Particle (ecology); Environmental chemistry; Mass spectrum; Environmental science; Laser ablation; Sea salt; Atmospheric sciences; Mineralogy; Analytical Chemistry (journal); Chemistry; Laser; Geology; Physics; Optics; Organic chemistry; Chromatography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002465648,0.0003211459,0.0002951484,0.0002550261,0.0002853478,0.0003097898,0.0006247822,0.0003432455,0.0008260817],"category_scores_gemma":[0.0005332324,0.0002075694,0.0003892527,0.0002423012,0.0002134064,0.0002698769,0.0001832264,0.0002034219,0.0002003738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001691596,"about_ca_system_score_gemma":0.001091049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2885249,"about_ca_topic_score_gemma":0.2106298,"domain_scores_codex":[0.999885,0.000018893,0.00000410851,0.00003285762,0.00002771318,0.00003149312],"domain_scores_gemma":[0.9998221,0.0000682548,0.00003050369,0.000011539,0.00005496459,0.00001268776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00009960379,0.00003253766,0.01281962,0.00002939353,0.00003874951,0.0001109609,0.00006099962,0.9729436,0.007310847,0.0008072375,0.0003345836,0.005411934],"study_design_scores_gemma":[0.000003810338,0.000008249259,0.002810796,5.255195e-7,0.000004830818,0.000008109431,0.00001006301,0.9964796,0.0005078408,0.00007135487,0.00009159988,0.000003259764],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826053,0.0001102919,0.01518204,0.000117504,0.000006660897,0.00001329316,0.0003496147,0.00015267,0.001462581],"genre_scores_gemma":[0.9973531,0.00004297976,0.00172096,0.000006017957,0.000002912579,0.000008374107,0.000144174,0.000009741985,0.0007118955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2885249,"threshold_uncertainty_score":0.5736909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004484633939724945,"score_gpt":0.176240155816779,"score_spread":0.171755521877054,"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."}}