{"id":"W4225574059","doi":"10.1029/2021gh000525","title":"Using Community Science to Better Understand Lead Exposure Risks","year":2022,"lang":"en","type":"article","venue":"GeoHealth","topic":"Noise Effects and Management","field":"Health Professions","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hamilton Health Sciences","funders":"National Science Foundation","keywords":"Environmental health; Logistic regression; Predictive power; Intervention (counseling); Medicine; Statistics; Mathematics; Physics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.005014147,0.0001098157,0.0001846419,0.0002172407,0.009698837,0.00001693748,0.0004479027,0.00003046576,0.000522906],"category_scores_gemma":[0.00007909249,0.0001045184,0.00002722719,0.0006712382,0.00009053963,0.00009708481,0.001277438,0.001192044,0.0001006268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001189048,"about_ca_system_score_gemma":0.0006445514,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009294125,"about_ca_topic_score_gemma":0.000802518,"domain_scores_codex":[0.9967707,0.001433526,0.000284872,0.0002346562,0.0004948655,0.0007813657],"domain_scores_gemma":[0.99876,0.0002217616,0.0001286444,0.0006024271,0.00006445206,0.0002226966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008353262,0.001689127,0.2592945,0.004168879,0.0001374848,0.00009588711,0.2320764,0.01154595,0.01625336,0.06370123,0.3188494,0.09135243],"study_design_scores_gemma":[0.004476047,0.002868681,0.3579765,0.0003916165,0.00009032871,0.000009209264,0.2149059,0.002448572,0.0001181941,0.01072552,0.404823,0.00116646],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798086,0.00005103725,0.002661179,0.005927354,0.001345458,0.001250981,0.00002690451,0.00008508196,0.008843428],"genre_scores_gemma":[0.9731582,0.000004334847,0.001386804,0.02450101,0.0001381503,0.00008369767,0.000005958493,0.00001838543,0.0007034104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.098682,"threshold_uncertainty_score":0.9973031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4001885442421698,"score_gpt":0.5229375060778658,"score_spread":0.122748961835696,"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."}}