{"id":"W4406949431","doi":"10.1109/ihtc61819.2024.10855074","title":"A Cost-Effective Air Quality Monitoring System for the Global South","year":2024,"lang":"en","type":"article","venue":"","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"National Research Foundation; International Development Research Centre","keywords":"Air quality index; Computer science; Quality (philosophy); Environmental science; Meteorology; Geography","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":[0.0009913413,0.0001193807,0.0001102885,0.000006764475,0.0002741774,0.00008253504,0.0001786271,0.00005036729,0.00003054575],"category_scores_gemma":[0.00008496873,0.00007439266,0.0001099955,0.0001993492,0.00008041527,0.0001133067,0.0001221233,0.00009932923,0.0004765444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006579431,"about_ca_system_score_gemma":0.00000735127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003348935,"about_ca_topic_score_gemma":0.000009722325,"domain_scores_codex":[0.9989376,0.00007370703,0.0001840535,0.0002969984,0.0002400469,0.0002676019],"domain_scores_gemma":[0.9991546,0.0005401036,0.00003434886,0.0001974811,0.000006981305,0.00006647709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001285398,0.00006495579,0.2986499,0.0007065558,0.0002407819,0.00001461983,0.007876028,0.01140146,0.0006283232,0.01478033,0.003458024,0.6620505],"study_design_scores_gemma":[0.001494194,0.0004687081,0.5968711,0.001135493,0.0003696692,0.00007246733,0.05027782,0.1114463,0.01796358,0.002031068,0.2161459,0.001723693],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4818539,0.000572066,0.4452763,0.001191818,0.008540403,0.005349396,0.0001468524,0.0019401,0.05512915],"genre_scores_gemma":[0.9966316,8.030773e-7,0.001009768,0.00001374431,0.0004773155,0.0004858055,0.000001071895,0.00001074597,0.001369124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6603268,"threshold_uncertainty_score":0.6125173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07618709262234243,"score_gpt":0.3525458763142777,"score_spread":0.2763587836919353,"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."}}