{"id":"W4416132475","doi":"10.1145/3736425.3770110","title":"A HOT Dataset: 150,000 Buildings for HVAC Operations Transfer Research","year":2025,"lang":"","type":"article","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"Canadian Institute for Advanced Research","keywords":"HVAC; Context (archaeology); ASHRAE 90.1; Occupancy; Energy consumption; Air conditioning; Building envelope; Transfer of learning; Efficient energy use","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005698973,0.00192203,0.0009995855,0.001812997,0.0006971393,0.001125325,0.00221463,0.001828839,0.006767856],"category_scores_gemma":[0.001869385,0.0003322465,0.00143911,0.002551722,0.0004732589,0.0009928216,0.001473691,0.00127194,0.009487828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128825,"about_ca_system_score_gemma":0.0007844518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01984746,"about_ca_topic_score_gemma":0.05021872,"domain_scores_codex":[0.999112,0.000173143,0.00007333495,0.0002819442,0.0002369612,0.0001226035],"domain_scores_gemma":[0.9993768,0.0001141805,0.00005324014,0.0002272789,0.0001565554,0.00007193642],"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":[0.0005728097,0.0008296995,0.02742067,0.001916031,0.0003443474,0.0004130687,0.0002762777,0.03658174,0.003456063,0.002598773,0.8601653,0.06542532],"study_design_scores_gemma":[0.0006465633,0.0006407668,0.1044038,0.0006007564,0.0002111214,0.001035788,0.001613709,0.1182233,0.009267662,0.008990062,0.7541116,0.0002548104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05342358,0.001387743,0.006113599,0.0006492301,0.000283938,0.0002538175,0.9244603,0.005929169,0.007498765],"genre_scores_gemma":[0.04077036,0.0002112976,0.005686604,0.0001430435,0.00004603762,0.0001645132,0.9513817,0.0001466691,0.00144972],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01984746,"threshold_uncertainty_score":0.03946388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04207599287839337,"score_gpt":0.3316734645625413,"score_spread":0.289597471684148,"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."}}