{"id":"W4312776326","doi":"10.2139/ssrn.4253967","title":"Product Aesthetic Design: A Machine Learning Augmentation","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Media and Visual Art","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Product design; Product (mathematics); Aesthetics; Computer science; Artificial intelligence; Mathematics; Art","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":[0.0008084044,0.000737696,0.0005800107,0.0009516249,0.0002866313,0.00107162,0.001092781,0.0008428161,0.01234763],"category_scores_gemma":[0.004363337,0.0003716553,0.0009632596,0.0007563315,0.0005524139,0.001370219,0.001041547,0.001180665,0.002374274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003686529,"about_ca_system_score_gemma":0.0004220381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009000238,"about_ca_topic_score_gemma":0.001558969,"domain_scores_codex":[0.9993808,0.0001602141,0.00003023674,0.0001818589,0.000213041,0.00003383298],"domain_scores_gemma":[0.9980953,0.0007505572,0.00009841882,0.0004767012,0.0005315663,0.00004736217],"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":[0.0003175632,0.00048063,0.002885458,0.0002959622,0.00006004705,0.00009234619,0.0001152012,0.07161362,0.01954059,0.00913156,0.01061995,0.884847],"study_design_scores_gemma":[0.00003059715,0.0002486875,0.002072337,0.0000528261,0.00005052821,0.0001925468,0.00004198422,0.970282,0.007793758,0.01035443,0.008860759,0.00001954914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08247076,0.0006246307,0.8829804,0.0007644331,0.0004266353,0.0003232754,0.0006569689,0.004142105,0.02761083],"genre_scores_gemma":[0.557611,0.0003907229,0.4232765,0.0003024564,0.0001724433,0.0002733821,0.0009561969,0.0003724686,0.01664483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01234763,"threshold_uncertainty_score":0.04130697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603225878929311,"score_gpt":0.2508420658368389,"score_spread":0.2348098070475458,"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."}}