{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006697378,0.0001709333,0.0002462415,0.000582449,0.001382391,0.002612225,0.000253487,0.001337539,0.002316267],"category_scores_gemma":[0.0007812473,0.0000900741,0.0002672756,0.0006255392,0.001606188,0.001221806,0.001155599,0.0008939813,0.0003899192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001261619,"about_ca_system_score_gemma":0.002455985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001585171,"about_ca_topic_score_gemma":0.002255118,"domain_scores_codex":[0.9995042,0.0002168365,0.00001932629,0.00004451493,0.0001299645,0.0000851588],"domain_scores_gemma":[0.999688,0.0001230848,0.00005829837,0.00003863082,0.00005243755,0.00003954624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001099652,0.0001341629,0.03347911,0.0005821573,0.00009163196,0.001906146,0.002706833,0.01145918,0.003999445,0.7914214,0.01326452,0.1408454],"study_design_scores_gemma":[0.00001349381,0.0002081055,0.06660457,0.0005937546,0.00005721117,0.00253843,0.008785181,0.004821396,0.001877806,0.435919,0.4785277,0.0000534051],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3835469,0.07560928,0.0115124,0.06517015,0.001037381,0.00004420584,0.0003821626,0.0001428594,0.4625546],"genre_scores_gemma":[0.9711157,0.01556907,0.001740289,0.0007595448,0.0003680113,0.00002150879,0.0001066641,0.0000162469,0.01030298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002612225,"threshold_uncertainty_score":0.009153724,"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."}}