{"id":"W7055243415","doi":"","title":"CIB Commits Up to $56 million for Energy Retrofits at University of Toronto","year":2022,"lang":"en","type":"other","venue":"","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Energy (signal processing); Renewable energy; Work (physics); Energy consumption; Efficient energy use","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00123003,0.001556631,0.0005924575,0.002158054,0.004457076,0.004782708,0.001429854,0.004154237,0.4784175],"category_scores_gemma":[0.002871429,0.0007349464,0.0008835025,0.001075082,0.001191588,0.001356123,0.00267828,0.003861921,0.1935712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009060862,"about_ca_system_score_gemma":0.01991479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4543474,"about_ca_topic_score_gemma":0.6771581,"domain_scores_codex":[0.9982989,0.0000660063,0.00002231431,0.000119707,0.0009892206,0.0005038223],"domain_scores_gemma":[0.9965658,0.0001653585,0.00005783371,0.0002169376,0.001480517,0.001513588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006236051,0.00003068056,0.0002631291,0.00002435823,0.000004740874,0.00004563342,0.00001829352,0.0001009177,0.0002926718,0.001986277,0.9837558,0.0134151],"study_design_scores_gemma":[0.00003027748,0.00002909312,0.001107839,0.00002294567,0.000004591655,0.00002642827,0.0001157038,0.0003302234,0.0002952317,0.0003834778,0.9976418,0.00001241871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002964622,0.0005868362,0.001206776,0.008260732,0.003587607,0.0002167458,0.006474827,0.002968047,0.9737338],"genre_scores_gemma":[0.006457916,0.0002320739,0.00037615,0.0009126735,0.0001673269,0.00003333672,0.002880613,0.0004295592,0.9885103],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4784175,"threshold_uncertainty_score":0.9034055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074707636256078,"score_gpt":0.2347807548488416,"score_spread":0.2240336784862809,"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."}}