{"id":"W4285822553","doi":"10.26868/25222708.2021.30433","title":"Investigating thermostat setpoint preferences in Canadian households","year":2021,"lang":"en","type":"article","venue":"Building Simulation Conference proceedings","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Setpoint; Thermostat; HVAC; Environmental science; Efficient energy use; Computer science; Engineering; Air conditioning; Mechanical engineering; Artificial intelligence; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001898437,0.0001859963,0.0001731468,0.0001727601,0.0001150627,0.0002164887,0.0001472006,0.0001524624,0.00008896487],"category_scores_gemma":[0.0001521064,0.0002117665,0.00002993527,0.0005895265,0.00002955932,0.000461731,0.00002802858,0.0002254862,0.000002695557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000188328,"about_ca_system_score_gemma":0.0002456878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003969779,"about_ca_topic_score_gemma":0.01206653,"domain_scores_codex":[0.9988295,0.00001004708,0.0002986648,0.0002742846,0.0001744386,0.0004130519],"domain_scores_gemma":[0.999422,0.00004852887,0.00004874878,0.00009240754,0.0002086905,0.0001795964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001055214,0.000006029462,0.03530667,0.00004441159,0.000009491841,0.000002307362,0.0008271955,0.9466144,0.002830418,0.01067719,0.00005230848,0.00362852],"study_design_scores_gemma":[0.000194036,0.000008599221,0.007480173,0.0001841272,0.000006755711,0.000004148355,0.0002107515,0.9792659,0.005574828,0.005810534,0.000987571,0.0002725227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871367,0.00009342426,0.006362707,0.0001471361,0.0001755788,0.0001094887,0.000004842575,0.000340159,0.005630006],"genre_scores_gemma":[0.9938836,0.0000360656,0.005768553,0.0001201945,0.00005305349,0.00002429161,0.00002089955,0.00003492535,0.00005844288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03265155,"threshold_uncertainty_score":0.8635588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02584944772706097,"score_gpt":0.2419019103699348,"score_spread":0.2160524626428738,"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."}}