{"id":"W7036281630","doi":"","title":"Assessment of the potentials to increase emissions reduction targets by the major GHGs emitters taking into consideration technological and political feasibility: In the framework of the project: \"Implikationen des Pariser Klimaschutzabkommens auf nationale Klimaschutzanstrengungen\"","year":2019,"lang":"en","type":"report","venue":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","topic":"South Asian Studies and Diaspora","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reduction (mathematics); Greenhouse gas; Distribution (mathematics); Politics; Quantitative assessment","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":[0.002953743,0.0002963609,0.0001315539,0.0009806793,0.0007591079,0.001602252,0.0003780336,0.000458151,0.003318502],"category_scores_gemma":[0.003277212,0.000116868,0.0002984711,0.001334672,0.0004582104,0.0007143898,0.001250058,0.0003776797,0.0002786756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002304463,"about_ca_system_score_gemma":0.004225374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01553425,"about_ca_topic_score_gemma":0.03660754,"domain_scores_codex":[0.998445,0.0005880802,0.00004471884,0.0000844307,0.0005852414,0.0002525067],"domain_scores_gemma":[0.9981036,0.0008054244,0.0002259031,0.00006954175,0.0007085808,0.00008688999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002125954,0.0005929352,0.3996069,0.001891828,0.0005137126,0.002212676,0.007479274,0.1018415,0.02757863,0.1157104,0.007950987,0.3324953],"study_design_scores_gemma":[0.0001210816,0.001909959,0.8113266,0.0003864621,0.0006382921,0.0005760762,0.03520143,0.02003694,0.03659484,0.01822175,0.0748982,0.00008844757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8534581,0.0009668667,0.004324475,0.001586878,0.00001722883,0.0003725132,0.001418284,0.00003704296,0.1378187],"genre_scores_gemma":[0.9917933,0.0005132175,0.002027149,0.00004090078,0.000005515243,0.00009528181,0.0002848216,0.00000536123,0.005234274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01553425,"threshold_uncertainty_score":0.03088766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05687939877255144,"score_gpt":0.3299064146927316,"score_spread":0.2730270159201802,"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."}}