{"id":"W2064723547","doi":"10.1145/2766929","title":"Elements of style","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Aesthetic Perception and Analysis","field":"Neuroscience","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Similarity (geometry); Salient; Computer science; Context (archaeology); Consistency (knowledge bases); Artificial intelligence; Matching (statistics); Similarity measure; Measure (data warehouse); Style (visual arts); Perception; Range (aeronautics); Pattern recognition (psychology); Mathematics; Data mining; Statistics; Psychology; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000118297,0.00006925268,0.00009369102,0.0001772123,0.00007432064,0.000009231307,0.0002231079,0.00003868206,0.0002265177],"category_scores_gemma":[0.00007137829,0.00006277923,0.0001006127,0.0005432286,0.000102263,0.00007066681,0.000002800668,0.0001091442,0.00007637743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001115825,"about_ca_system_score_gemma":0.00002321361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001426031,"about_ca_topic_score_gemma":0.00001245472,"domain_scores_codex":[0.9992177,0.00005574284,0.0001692979,0.0001598313,0.000289543,0.0001078322],"domain_scores_gemma":[0.9994271,0.00002308984,0.00004987464,0.0003665344,0.00004217997,0.00009121458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006149822,0.008559919,0.008263174,0.0000943352,0.0001222869,0.00005478723,0.01023584,0.005455962,0.4602999,0.03470997,0.005521295,0.4660675],"study_design_scores_gemma":[0.01191034,0.003516603,0.009178162,0.000193275,0.0009014333,0.0001445661,0.008137217,0.02517669,0.6756951,0.09250651,0.1700541,0.002585997],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8790719,0.00001270577,0.1145713,0.002228272,0.0002270526,0.000137188,0.00005163493,0.0001262093,0.003573718],"genre_scores_gemma":[0.9979097,0.00008782901,0.0007116058,0.0008022157,0.000005661429,0.000006199996,9.69657e-7,0.000007227758,0.0004685977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4634815,"threshold_uncertainty_score":0.2560063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08664182901158185,"score_gpt":0.3153371207410397,"score_spread":0.2286952917294579,"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."}}