{"id":"W4400886049","doi":"10.1016/j.dib.2024.110755","title":"Dataset of images for visual and non-visual analysis of colour applications in architecture","year":2024,"lang":"en","type":"article","venue":"Data in Brief","topic":"Color perception and design","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Sentinelle Nord, Université Laval; Canada First Research Excellence Fund; Université Laval","keywords":"Luminance; Computer science; Daylight; Computer vision; Brightness; Computer graphics (images); GLARE; Artificial intelligence; Photopic vision; High dynamic range; Dynamic range; Optics","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":[0.0003304827,0.00006468752,0.0002129578,0.0004543007,0.00001087747,0.00001299016,0.0001992599,0.00005536368,0.000324478],"category_scores_gemma":[0.00003171958,0.00006123166,0.00002531812,0.000762689,0.00007889833,0.00005685459,0.0001039647,0.00008093767,0.000005254053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007865512,"about_ca_system_score_gemma":0.00002292714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007104133,"about_ca_topic_score_gemma":0.0008903003,"domain_scores_codex":[0.9992227,0.00004340919,0.0002669857,0.000307936,0.00006156776,0.00009738129],"domain_scores_gemma":[0.9992082,0.0002949001,0.00004207971,0.0004171867,0.00001334928,0.00002434462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001181989,0.002985049,0.1448164,0.0009737166,0.002025882,0.000042729,0.008196646,0.0002805519,0.02925458,0.005221313,0.6357507,0.1692704],"study_design_scores_gemma":[0.000983209,0.0002219348,0.786505,0.00003439808,0.000494947,0.000003789411,0.001068355,0.01338744,0.0001740671,0.000248187,0.1966825,0.0001961416],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7538345,0.0004950652,0.06036775,0.000386589,0.00009169908,0.001035158,0.1834069,0.00002248817,0.0003598151],"genre_scores_gemma":[0.9522805,0.00001808359,0.00081589,0.00009253543,0.00002297043,0.00009362674,0.04660809,0.000007725399,0.00006053618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6416886,"threshold_uncertainty_score":0.3552807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04090295107916211,"score_gpt":0.4274512089043832,"score_spread":0.3865482578252211,"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."}}