{"id":"W7015035569","doi":"","title":"Satellites, Coding &amp; Air Sensors: Air quality research using PurpleAir sensors, TEMPO and Python","year":2024,"lang":"en","type":"article","venue":"ValpoScholar (Valparaiso University)","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Python (programming language); Air quality index; Coding (social sciences); Quality assurance; Data quality; Software","routes":{"ca_aff":false,"ca_fund":false,"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":[0.001473194,0.001049215,0.00052683,0.0008807342,0.0004478402,0.00177474,0.001871902,0.0004936194,0.04268396],"category_scores_gemma":[0.004685063,0.000617823,0.0008670052,0.001253731,0.0005927788,0.002397629,0.001557257,0.00143286,0.03064405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006512794,"about_ca_system_score_gemma":0.001062706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003256799,"about_ca_topic_score_gemma":0.003146211,"domain_scores_codex":[0.998869,0.0001626889,0.00008522961,0.0002170735,0.0005957903,0.0000700986],"domain_scores_gemma":[0.9982134,0.0004018949,0.0001575726,0.0005432823,0.0005741733,0.000109758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003840451,0.0001434658,0.005056846,0.001000165,0.0001517182,0.0002472232,0.0005792314,0.01535914,0.02183621,0.02584342,0.6428143,0.2865843],"study_design_scores_gemma":[0.0001534648,0.0001137529,0.00425288,0.0001809422,0.00005690614,0.0002199262,0.0001676442,0.1177607,0.05016953,0.02243372,0.804355,0.0001357704],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.00754989,0.0003872966,0.4374887,0.001443912,0.000604857,0.0003802793,0.03053698,0.4789863,0.04262163],"genre_scores_gemma":[0.1114276,0.001693353,0.6838959,0.001891769,0.000332516,0.001233602,0.05877929,0.07209437,0.06865159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04268396,"threshold_uncertainty_score":0.142792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1520340393011052,"score_gpt":0.3591161500200465,"score_spread":0.2070821107189413,"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."}}