{"id":"W6912793913","doi":"10.5281/zenodo.4139309","title":"Environmental problems of Russia and potential of its power industry for their solution","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Power Generation Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Government (linguistics); Global warming; Politics; Electric power industry; Energy policy; Energy supply; Field (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007896123,0.00007512658,0.00009394283,0.00006024112,0.000177775,0.00003345986,0.0002117721,0.00008367215,0.0006689907],"category_scores_gemma":[0.00008028904,0.00007827068,0.00002146798,0.0001165251,0.00008616598,0.0001317316,0.0002416394,0.0001407087,0.00004764711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002582711,"about_ca_system_score_gemma":8.051693e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.681163e-7,"about_ca_topic_score_gemma":1.093394e-8,"domain_scores_codex":[0.9994578,0.0000223735,0.0001648416,0.000133291,0.00009882241,0.0001228186],"domain_scores_gemma":[0.9997362,0.0000053257,0.00005176274,0.0001113953,0.00004800992,0.00004727141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003288781,0.00003785437,0.000005104916,0.0002104393,0.00004494511,5.919293e-7,0.001110516,0.008018212,0.9455706,0.001259178,0.008556465,0.03515319],"study_design_scores_gemma":[0.001258804,0.0008195059,0.0009943038,0.00005480477,0.00002309322,0.00002740843,0.001391856,0.03902313,0.4483284,0.0003902341,0.5073483,0.0003400942],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6936251,0.001169821,0.2930858,0.001212993,0.0001470772,0.00148687,0.001456123,0.001879656,0.005936561],"genre_scores_gemma":[0.99878,0.0001237632,0.0005895399,0.00001232688,0.00002056431,6.021593e-8,0.0001515645,0.0003050737,0.00001717594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4987919,"threshold_uncertainty_score":0.7324979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02144859024339809,"score_gpt":0.1983553418575256,"score_spread":0.1769067516141275,"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."}}