{"id":"W4381163856","doi":"10.32920/23541831","title":"Towards Window State Detection Using Image Processing","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Window (computing); Thresholding; Computer science; Occupancy; Energy (signal processing); Image (mathematics); Image processing; Artificial intelligence; Data mining; Computer vision; Engineering; Statistics; Mathematics; Architectural 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":[0.0006024084,0.000913461,0.0007514338,0.001746166,0.0002691854,0.001742814,0.00109125,0.0008970072,0.002240537],"category_scores_gemma":[0.001918137,0.0005669105,0.0007641602,0.001090902,0.0004920018,0.001586302,0.0009299399,0.0009825858,0.00146774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003431384,"about_ca_system_score_gemma":0.0005959189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00281428,"about_ca_topic_score_gemma":0.002520765,"domain_scores_codex":[0.9995036,0.00006226962,0.00002601732,0.0001485355,0.0001940043,0.00006561827],"domain_scores_gemma":[0.9991149,0.0002419215,0.00008673375,0.0001634477,0.0003535295,0.00003946079],"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":[0.000253832,0.0001895133,0.002772709,0.0001681881,0.00006729273,0.0001146051,0.0001473845,0.0309533,0.257134,0.004578767,0.002994444,0.700626],"study_design_scores_gemma":[0.00001554685,0.0001120228,0.003496955,0.00003200367,0.00003367867,0.0001854927,0.0001031487,0.8247654,0.1615209,0.003986751,0.0057074,0.00004060719],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01969018,0.0001928209,0.9772893,0.00007224926,0.00003395021,0.00005310683,0.00009297297,0.001605495,0.0009698382],"genre_scores_gemma":[0.1432329,0.0004074426,0.8535683,0.00006226296,0.00003291821,0.00007638751,0.0003334985,0.0002182566,0.002067934],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00281428,"threshold_uncertainty_score":0.007495344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02465560734254832,"score_gpt":0.246534022324141,"score_spread":0.2218784149815927,"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."}}