{"id":"W4220741458","doi":"10.1007/s11042-022-11966-5","title":"Collecting a database for emotional responses to simple and patterned two-color images","year":2022,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Color perception and design","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Chrominance; Hue; Computer science; Lightness; Artificial intelligence; Computer vision; Luminance","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":[0.0006358466,0.0006795822,0.0006285587,0.00255974,0.0004602388,0.0004887916,0.0007283558,0.0007576828,0.007066672],"category_scores_gemma":[0.004344663,0.0002336062,0.0004326972,0.00138079,0.0002113317,0.0005402993,0.0006766807,0.0004443196,0.004498412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003041704,"about_ca_system_score_gemma":0.0004242637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00162213,"about_ca_topic_score_gemma":0.003385297,"domain_scores_codex":[0.999271,0.0001554959,0.00009879351,0.0001739141,0.0002327572,0.00006809342],"domain_scores_gemma":[0.9952273,0.001376977,0.0003695976,0.001205292,0.001461886,0.000358936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004322361,0.003801656,0.1032857,0.002474913,0.0002749357,0.001789001,0.002538511,0.002523687,0.2925824,0.001051389,0.07129198,0.5140635],"study_design_scores_gemma":[0.0002668337,0.001757435,0.739075,0.0002576062,0.0004007402,0.004250029,0.003700725,0.01582773,0.1530677,0.001573472,0.07952555,0.0002971769],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.7947773,0.001029289,0.07251596,0.0003095918,0.0001956201,0.004162343,0.1039227,0.00575716,0.01732997],"genre_scores_gemma":[0.7287462,0.001127201,0.1081021,0.0005470325,0.0001716968,0.006465106,0.1393307,0.0009584207,0.01455168],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.007066672,"threshold_uncertainty_score":0.02364033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09295747299032539,"score_gpt":0.3921341889116847,"score_spread":0.2991767159213593,"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."}}