{"id":"W4399259692","doi":"10.1007/s00371-024-03492-2","title":"ARF-Net: a multi-modal aesthetic attention-based fusion","year":2024,"lang":"en","type":"article","venue":"The Visual Computer","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Modal; Fusion; Computer science; Net (polyhedron); Artificial intelligence; Aesthetics; Art; Mathematics; Materials science; Philosophy; Linguistics; Geometry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004441004,0.0001965713,0.0001377409,0.0001971084,0.0002993882,0.00053254,0.0006419206,0.0000708156,0.000044555],"category_scores_gemma":[0.000004094897,0.000131394,0.00020046,0.0006676299,0.00008976481,0.0002993355,0.0002231968,0.0002418976,0.001092477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005069325,"about_ca_system_score_gemma":0.0000574617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002542025,"about_ca_topic_score_gemma":0.000007270071,"domain_scores_codex":[0.9983559,0.0001932582,0.0002701291,0.0004920257,0.0003863833,0.0003023298],"domain_scores_gemma":[0.9993193,0.00006906138,0.00004741414,0.0004094751,0.00006818637,0.00008663398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004727802,0.001027661,0.0004291362,0.0001698206,0.00007730647,0.0001587631,0.002197467,0.004403635,0.01328018,0.04621521,0.007149277,0.9248443],"study_design_scores_gemma":[0.000309469,0.0002908033,0.003313277,0.000076998,0.000009984285,0.00005590211,0.00001065814,0.988749,0.0003583319,0.0004970692,0.006132956,0.0001955948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1691065,0.0001178825,0.8255134,0.002280294,0.002009399,0.0001993709,0.000001026338,0.0006797789,0.00009236716],"genre_scores_gemma":[0.9905717,0.000004393179,0.007479645,0.001064173,0.0002351078,0.00002279278,0.000005425246,0.00001975665,0.0005970136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9843453,"threshold_uncertainty_score":0.9996853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01999869903814298,"score_gpt":0.2993474859594429,"score_spread":0.2793487869212999,"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."}}