{"id":"W4281659215","doi":"10.1038/s41597-022-01314-5","title":"Indoor heat measurement data from low-income households in rural and urban South Asia","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government College University, Lahore; Department for International Development; International Development Research Centre","keywords":"Geography; Socioeconomic status; Urban heat island; Heat stress; South asia; Socioeconomics; Rural area; Thermal comfort; Environmental science; Environmental health; Meteorology; Population; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0003287814,0.0003418292,0.0003859707,0.0008158287,0.0003093171,0.0004533814,0.0005647883,0.0003521934,0.002490499],"category_scores_gemma":[0.0008586298,0.0001763879,0.0003866673,0.002766376,0.0002212545,0.0003515029,0.0007390223,0.0003457952,0.001456114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003953833,"about_ca_system_score_gemma":0.0006382016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04746629,"about_ca_topic_score_gemma":0.06045964,"domain_scores_codex":[0.9996457,0.00006757485,0.00005161491,0.00009120348,0.00007799656,0.00006587755],"domain_scores_gemma":[0.9989177,0.0001631669,0.0002111452,0.0002217176,0.0003828136,0.0001034526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004346566,0.0003284897,0.9181044,0.000922062,0.0002168024,0.0003385242,0.001953426,0.004052578,0.003326214,0.0005531396,0.04091568,0.02885398],"study_design_scores_gemma":[0.00002854404,0.00005369589,0.9785715,0.00006838373,0.00004353866,0.0001054036,0.002391864,0.002069388,0.001208736,0.0001384107,0.01529663,0.00002392085],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.7345684,0.0001778556,0.001149784,0.0002364274,0.00002780995,0.0001087514,0.2583919,0.0002022489,0.005136792],"genre_scores_gemma":[0.646937,0.0003131739,0.002663876,0.000142672,0.00002363754,0.0004445643,0.347228,0.0000424062,0.002204689],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.04746629,"threshold_uncertainty_score":0.09437996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1739709056250032,"score_gpt":0.3067096017835971,"score_spread":0.1327386961585939,"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."}}