{"id":"W4396919061","doi":"10.1145/3659593","title":"AeroSense: Sensing Aerosol Emissions from Indoor Human Activities","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Infection Control and Ventilation","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Universitas Brawijaya","keywords":"Aerosol; Environmental science; Remote sensing; Meteorology; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001079817,0.0001917808,0.0003049769,0.0002132198,0.0002505499,0.000109811,0.0002179371,0.0001798871,0.00002462504],"category_scores_gemma":[0.0006471344,0.0001248531,0.0001328435,0.0002530266,0.0002145684,0.0002750654,0.0004010813,0.0005741415,0.000006475635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008492647,"about_ca_system_score_gemma":0.00002663177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006871104,"about_ca_topic_score_gemma":0.000003859789,"domain_scores_codex":[0.9990247,0.000006608341,0.0002384529,0.0003401504,0.0001923995,0.0001976933],"domain_scores_gemma":[0.9992006,0.0002109832,0.0001403964,0.0002817414,0.0001401604,0.00002613247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002255549,0.00009038519,0.002589196,0.0001587745,0.0001675925,0.000003890404,0.0006271496,0.000002039941,0.9583507,0.0004322598,0.00187923,0.0354732],"study_design_scores_gemma":[0.0003356158,0.0005676314,0.001665389,0.002087754,0.0001209293,0.00005454926,0.005708293,0.0003848762,0.9816444,0.00571504,0.001576498,0.00013906],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938453,0.0005895834,0.00001891306,0.00151849,0.0003044114,0.0004959255,0.00001318684,0.0006272997,0.002586844],"genre_scores_gemma":[0.9983252,0.0001432609,0.0002215868,0.00005621174,0.0001028971,0.00005852769,0.000001840068,0.00002428974,0.001066228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03533414,"threshold_uncertainty_score":0.5091362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409937622054364,"score_gpt":0.2871145682458979,"score_spread":0.2730151920253542,"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."}}