{"id":"W3028590447","doi":"10.48550/arxiv.2005.09616","title":"Group segmentation and heterogeneity in the choice of cooking fuels in post-earthquake Nepal","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ethnic group; Diversity (politics); Psychological intervention; Market segmentation; Geography; Population; Cultural diversity; Demographic economics; Economics; Business; Demography; Psychology; Political science; Marketing; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006089325,0.0001396592,0.0002382739,0.0006076828,0.0006713543,0.0007680287,0.0002701235,0.000245842,0.001689386],"category_scores_gemma":[0.003141592,0.0001295422,0.0002639722,0.0009306499,0.0007339746,0.0005117354,0.001114822,0.0003644685,0.000136676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003912282,"about_ca_system_score_gemma":0.0003525846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01591103,"about_ca_topic_score_gemma":0.02366635,"domain_scores_codex":[0.999523,0.0002189048,0.00002412211,0.00009409423,0.00004414551,0.00009582141],"domain_scores_gemma":[0.9986075,0.00064669,0.0003753485,0.0001630706,0.0001016396,0.0001057593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001817327,0.00009358929,0.9824655,0.00002308111,0.0001576205,0.0002142807,0.006429946,0.0004910184,0.001352951,0.0004972515,0.0001997901,0.007893212],"study_design_scores_gemma":[0.000002948223,0.00005111868,0.9921277,0.00001080703,0.00001931809,0.00006972106,0.005711711,0.001187396,0.0001857233,0.0003445638,0.00028051,0.000008556079],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995408,0.00001218305,0.0001041664,0.00002173159,7.969617e-7,0.00000221308,0.00004135392,8.834907e-7,0.0002759012],"genre_scores_gemma":[0.999759,0.000009883182,0.00005916335,0.000005914673,7.552889e-7,0.000003366132,0.00006515315,9.227749e-7,0.00009586533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01591103,"threshold_uncertainty_score":0.03163683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06529074167200992,"score_gpt":0.197229102873529,"score_spread":0.1319383612015191,"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."}}