{"id":"W3173168440","doi":"10.1016/j.buildenv.2021.108104","title":"Residential thermostat usability: Comparing manual, programmable, and smart devices","year":2021,"lang":"en","type":"article","venue":"Building and Environment","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Carleton University","keywords":"Thermostat; Usability; Setpoint; Computer science; Human–computer interaction; Energy consumption; Engineering; Simulation; Electrical engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009880595,0.0001094422,0.0001178828,0.00002180373,0.0001102005,0.00007854828,0.00003746219,0.00004784657,0.00002779797],"category_scores_gemma":[0.000003398731,0.000112912,0.0000176551,0.00004005381,0.00004265342,0.00009123387,0.00007378276,0.0000769644,0.000001052429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002761137,"about_ca_system_score_gemma":0.000003283187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000223382,"about_ca_topic_score_gemma":0.00001438274,"domain_scores_codex":[0.9994031,0.00001812501,0.0001252117,0.0001978652,0.00009214888,0.0001635895],"domain_scores_gemma":[0.9997733,0.00001978394,0.00001551271,0.0001292464,0.000003110018,0.00005904686],"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":[0.00001289167,0.00005091963,0.06100812,0.0001708323,0.0001002589,0.00001979124,0.0002683298,0.8654847,0.005017748,0.001664469,0.0002042742,0.06599773],"study_design_scores_gemma":[0.00128528,0.00008618695,0.1287563,0.0002300622,0.0001681069,0.0001360311,0.0004491833,0.7572504,0.02584,0.002096013,0.08266962,0.001032872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804943,0.002198943,0.01652653,0.00008626367,0.00008784883,0.00005487404,9.988094e-7,0.0001032603,0.0004469772],"genre_scores_gemma":[0.9892877,0.001317335,0.009192799,0.0000278118,0.00003263472,0.00001401283,0.000008464618,0.00001733404,0.0001019436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1082343,"threshold_uncertainty_score":0.4604419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01018894232334987,"score_gpt":0.202418327429229,"score_spread":0.1922293851058791,"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."}}