{"id":"W2048647542","doi":"10.1145/2770879","title":"Where2Stand","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Intelligent Systems and Technology","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Computer science; Photography; Set (abstract data type); Artificial intelligence; Construct (python library); Portrait; Computer vision; Visual arts; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001752085,0.0001069428,0.0001329076,0.0003876835,0.0001249534,0.00008388384,0.0003937923,0.000142379,0.000008930474],"category_scores_gemma":[0.00002448425,0.00009274235,0.00002943642,0.0005647895,0.00005887048,0.000161391,0.00001607659,0.0001664179,0.0001237596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004779245,"about_ca_system_score_gemma":0.00002430248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000504255,"about_ca_topic_score_gemma":0.0000160441,"domain_scores_codex":[0.9991485,0.00003362611,0.0002092001,0.0002871637,0.0001549452,0.0001665129],"domain_scores_gemma":[0.9991892,0.00002333001,0.00004794959,0.0005329479,0.000111559,0.00009502564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000253028,0.0003605775,0.0004778607,0.00004697846,0.00009983101,0.00002674333,0.0007083432,0.0007376163,0.0009740081,0.3269567,0.0008914872,0.6686945],"study_design_scores_gemma":[0.003036919,0.006318319,0.0002166762,0.0003802979,0.00008743544,0.002363636,0.0110929,0.111763,0.0759739,0.1837718,0.6030388,0.001956254],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0115829,0.0004237825,0.9835933,0.001997548,0.001138638,0.0001586849,0.000001535303,0.0004733871,0.0006302512],"genre_scores_gemma":[0.9966441,0.00009524343,0.00193692,0.00004438548,0.00001545774,0.000047149,3.193589e-7,0.000006567576,0.001209789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9850613,"threshold_uncertainty_score":0.3781923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04655803020375763,"score_gpt":0.2875559595514385,"score_spread":0.2409979293476809,"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."}}