{"id":"W4214863837","doi":"10.2172/1560613","title":"R&amp;D and Implementation Outcomes from the U.S.-India Bilateral Center for Building Energy Research and Development Program","year":2019,"lang":"en","type":"report","venue":"Lawrence Berkeley National Laboratory","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Department of Science and Technology, Ministry of Science and Technology, India; U.S. Department of Energy","keywords":"Benchmarking; Software deployment; Capacity building; Joint (building); Key (lock); Research center; Engineering management; Efficient energy use; Business; Engineering; Architectural engineering; Computer science; Political science; Economic growth; Marketing; Economics; Computer security; Software engineering","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":[0.01793619,0.0008668157,0.0003161957,0.00207011,0.002210946,0.004765558,0.001139621,0.00101937,0.006667955],"category_scores_gemma":[0.0122852,0.0002938423,0.0005267662,0.003379839,0.001261656,0.001450484,0.006778157,0.001464908,0.001938214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004718826,"about_ca_system_score_gemma":0.02398339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02452206,"about_ca_topic_score_gemma":0.03763693,"domain_scores_codex":[0.9829822,0.004340981,0.0005705744,0.0009306891,0.007699384,0.003476166],"domain_scores_gemma":[0.9759398,0.003700132,0.001487745,0.002849313,0.009277148,0.006745858],"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":[0.0009436636,0.003521679,0.0857987,0.001137666,0.0001660761,0.0009574182,0.005286458,0.01363974,0.01741164,0.05212038,0.08664603,0.7323706],"study_design_scores_gemma":[0.0002620722,0.004213754,0.3098415,0.0002652752,0.0001905045,0.0008311998,0.01880383,0.005642249,0.05622467,0.006710283,0.5967456,0.0002689632],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5094525,0.002214675,0.02473769,0.01952389,0.0005260226,0.002219289,0.009001873,0.00284602,0.429478],"genre_scores_gemma":[0.8750362,0.001754343,0.02632206,0.001463632,0.00007431201,0.000813679,0.008200342,0.0004510838,0.08588441],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02452206,"threshold_uncertainty_score":0.09485674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06608516919305976,"score_gpt":0.3661899490772547,"score_spread":0.3001047798841949,"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."}}