{"id":"W2735646247","doi":"","title":"Solid Waste Management in Chennai: Lessons from Exnora","year":2016,"lang":"en","type":"article","venue":"˜The œinnovation journal","topic":"Urban and Rural Development Challenges","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Municipal solid waste; Garbage; Per capita; Business; Waste disposal; Megacity; Population; Waste collection; Municipal corporation; Local government; Waste management; Environmental planning; Agricultural economics; Engineering; Geography; Economics; Economy; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.000920749,0.0006975636,0.000338716,0.001401875,0.003277274,0.00495258,0.001809803,0.001546001,0.006208143],"category_scores_gemma":[0.001078324,0.0002749156,0.0004851399,0.003334602,0.002117351,0.002048688,0.00305775,0.002396148,0.0009977448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00841823,"about_ca_system_score_gemma":0.01578182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1542863,"about_ca_topic_score_gemma":0.2730714,"domain_scores_codex":[0.9991357,0.0002617387,0.00007280653,0.0001089282,0.0002117996,0.0002091086],"domain_scores_gemma":[0.9986951,0.0003146943,0.00007835116,0.00007664171,0.0005170481,0.0003182156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002779991,0.0008925288,0.03845808,0.007075563,0.0001428899,0.01188544,0.05612098,0.003036136,0.004652712,0.04042773,0.06856535,0.7684646],"study_design_scores_gemma":[0.00003311475,0.0006164265,0.04964452,0.004293766,0.0001144419,0.00330938,0.1471372,0.0009887393,0.005366931,0.009053424,0.7792733,0.0001687214],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3470187,0.2205783,0.002790775,0.1693239,0.002089469,0.0004280527,0.001207888,0.0003441774,0.2562189],"genre_scores_gemma":[0.7609581,0.1672541,0.00681604,0.02000994,0.0003819823,0.0001286563,0.0005997368,0.0001067088,0.04374474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1542863,"threshold_uncertainty_score":0.3067766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06391010949531302,"score_gpt":0.3434553035137711,"score_spread":0.2795451940184581,"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."}}