{"id":"W7036642494","doi":"","title":"Combined heat and power generation for residential applications","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Plant Taxonomy and Phylogenetics","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity generation; Power (physics); Heat generation; Temperature measurement","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003160895,0.0002841964,0.0003204934,0.0005785184,0.001034749,0.0005135518,0.0006014419,0.0003647537,0.01693072],"category_scores_gemma":[0.0005126184,0.0001414583,0.0003150897,0.001220039,0.0002490444,0.0006648499,0.0005130693,0.0004163752,0.002567355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006029423,"about_ca_system_score_gemma":0.0006878505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003604898,"about_ca_topic_score_gemma":0.01338851,"domain_scores_codex":[0.9995846,0.00008425995,0.000008948829,0.00004512351,0.0002183922,0.00005865246],"domain_scores_gemma":[0.9996921,0.00006968751,0.0000122313,0.00005331425,0.000140618,0.00003198893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002232363,0.0007649087,0.02018782,0.0009377429,0.0001172672,0.0009899156,0.0004264352,0.04642145,0.1946353,0.004811242,0.01572939,0.7127461],"study_design_scores_gemma":[0.0006466857,0.004311417,0.1466797,0.0001755203,0.0003542305,0.002794034,0.001561518,0.1573415,0.5000693,0.009299747,0.1765811,0.000185351],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8328938,0.002106473,0.08273405,0.0005371448,0.000176258,0.0003604047,0.001183853,0.001669746,0.07833818],"genre_scores_gemma":[0.9814389,0.0003331666,0.009808675,0.00002375209,0.00002591789,0.00006863502,0.0003427921,0.00007197561,0.007886087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01693072,"threshold_uncertainty_score":0.05663896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437647042270526,"score_gpt":0.2177795565289937,"score_spread":0.1934030861062885,"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."}}