{"id":"W1968189575","doi":"10.1117/12.864685","title":"Bioaerosol standoff detection and correlation assessment with concentration and viability point sensors","year":2010,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Bioaerosol; Indoor bioaerosol; Analytical Chemistry (journal); Materials science; Particle size; Remote sensing; Aerosol; Chemistry; Physics; Chromatography; Meteorology; Environmental chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006941471,0.0001716053,0.0001831633,0.00001628439,0.0001258207,0.00008500888,0.000152854,0.0001187092,0.00001053702],"category_scores_gemma":[0.0002563837,0.0001340606,0.00009117554,0.0001308729,0.0003851393,0.0005010505,0.0000893187,0.0002923431,3.600237e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157994,"about_ca_system_score_gemma":0.000008171559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002971176,"about_ca_topic_score_gemma":0.000001162315,"domain_scores_codex":[0.9987335,2.523607e-8,0.0003391246,0.0002991425,0.0004278376,0.000200374],"domain_scores_gemma":[0.9992809,0.0001143786,0.0002445458,0.00003441031,0.0002329283,0.0000928911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008642424,0.00005802688,0.03640387,0.0001403315,0.00006928913,3.117137e-8,0.0003913671,0.0002282071,0.9308003,0.03029888,0.00004279791,0.001480449],"study_design_scores_gemma":[0.002758045,0.001242626,0.1780406,0.0002675713,0.0002473011,0.00006763294,0.003854554,0.4363504,0.3733279,0.002266066,0.0008124265,0.0007648725],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977331,0.000006086329,0.0002674362,0.0006445509,0.0001417057,0.0004100148,0.00001009173,0.00004320218,0.0007438625],"genre_scores_gemma":[0.9489527,0.00001223636,0.05082274,0.00001457328,0.0001111985,0.00003800484,0.00000191224,0.00001721815,0.00002938654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5574724,"threshold_uncertainty_score":0.5466833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008117677899566245,"score_gpt":0.2233323364584393,"score_spread":0.2152146585588731,"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."}}