{"id":"W2759030807","doi":"10.2172/816074","title":"Energy star product specification development framework: Using data and analysis to make program decisions","year":2003,"lang":"en","type":"report","venue":"","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; LG Electronics; Lawrence Berkeley National Laboratory; U.S. Environmental Protection Agency","keywords":"New product development; Product (mathematics); Process (computing); Agency (philosophy); Government (linguistics); Business; Process management; Computer science; Marketing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.1297055,0.002333963,0.001748526,0.02250508,0.002883825,0.01347217,0.005831819,0.002171854,0.007206563],"category_scores_gemma":[0.1459576,0.002113378,0.001958967,0.01616499,0.002532348,0.0106754,0.005050544,0.003355192,0.00493783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008881826,"about_ca_system_score_gemma":0.04294639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04714915,"about_ca_topic_score_gemma":0.03783603,"domain_scores_codex":[0.9086517,0.04476679,0.01504364,0.003931798,0.02607899,0.001527076],"domain_scores_gemma":[0.8094544,0.09733301,0.01408138,0.01938352,0.05728038,0.002467311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000225215,0.0005648728,0.01642702,0.002212767,0.0002491447,0.0008563495,0.004905002,0.03009772,0.002770682,0.207206,0.2063196,0.5281657],"study_design_scores_gemma":[0.0002534878,0.000339587,0.01056677,0.004093058,0.000190297,0.0004640644,0.005820247,0.07722294,0.007857649,0.1172741,0.775517,0.0004007905],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.007305304,0.001045872,0.87008,0.008584006,0.0002276091,0.008663796,0.03265858,0.0114481,0.05998675],"genre_scores_gemma":[0.01650307,0.0006495995,0.9460118,0.0004349913,0.00003801845,0.004835023,0.02834446,0.000690076,0.002493036],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1297055,"threshold_uncertainty_score":0.6859567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1058915289570757,"score_gpt":0.3635251157774039,"score_spread":0.2576335868203282,"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."}}