{"id":"W7019901627","doi":"","title":"India’s Long-Term Hydrofluorocarbon Emissions: A detailed cross-sectoral analysis within an integrated assessment modelling framework","year":2015,"lang":"en","type":"other","venue":"IIASA PURE (International Institute of Applied Systems Analysis)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Foundation (evidence); Sustainability; Energy demand; Energy analysis; Sustainable energy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005243751,0.0004017931,0.0003643644,0.0007996007,0.0003180114,0.001470544,0.0006524328,0.0004366284,0.001694982],"category_scores_gemma":[0.0006947347,0.0002897456,0.001259677,0.002224486,0.0002958888,0.0008278437,0.0008110366,0.0005690571,0.0003394011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003113245,"about_ca_system_score_gemma":0.0025914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.13296,"about_ca_topic_score_gemma":0.1122072,"domain_scores_codex":[0.9996676,0.0001046104,0.00001534181,0.00004146311,0.00009582075,0.00007507118],"domain_scores_gemma":[0.9996694,0.0001181174,0.00004088456,0.00004619059,0.0001074719,0.00001792467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002604334,0.0002155321,0.05056907,0.0002138705,0.0005346959,0.0007380788,0.0004312712,0.8493013,0.003508343,0.05018108,0.00715051,0.03689582],"study_design_scores_gemma":[0.00005988101,0.0002755444,0.1378902,0.0001518588,0.0008864499,0.0002979186,0.00184789,0.7942477,0.007556341,0.02423373,0.0323717,0.0001808204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8632371,0.001107319,0.0284149,0.002076063,0.0000516345,0.0001202272,0.007733529,0.000349993,0.09690915],"genre_scores_gemma":[0.9858148,0.0007104074,0.005488033,0.00006897404,0.000008683649,0.00004721472,0.002169402,0.00004038319,0.005652143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.13296,"threshold_uncertainty_score":0.2643722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03695537300589521,"score_gpt":0.3354602037432907,"score_spread":0.2985048307373955,"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."}}