{"id":"W2071630209","doi":"10.1145/2677199.2680559","title":"Mapping Place","year":2015,"lang":"en","type":"article","venue":"","topic":"Museums and Cultural Heritage","field":"Arts and Humanities","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Visitor pattern; Exhibition; Computer science; Context (archaeology); Process (computing); Human–computer interaction; Embodied cognition; Multimedia; Visual arts; Art; Artificial intelligence; History","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":["insufficient_payload"],"category_scores_codex":[0.00004114831,0.00003548121,0.00003852327,0.000009011472,0.00005610774,0.00006506664,0.00004175188,0.000007800747,0.006653194],"category_scores_gemma":[0.000003959715,0.00002245218,0.00001595603,0.000006613909,0.00002382743,0.00009785117,0.00001263695,0.00002390202,0.0007841751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007089523,"about_ca_system_score_gemma":0.000006342582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002224248,"about_ca_topic_score_gemma":0.0005178271,"domain_scores_codex":[0.9997694,0.000002878304,0.00004831044,0.00004917247,0.00005747278,0.00007280332],"domain_scores_gemma":[0.9998595,0.000003453388,0.000008741652,0.00004915433,0.00003298974,0.00004612516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001777369,0.000007797362,0.0000185986,0.000002826067,0.000003444251,0.000001653966,0.04029911,6.222699e-7,0.00001459993,0.7375536,0.2210602,0.001035819],"study_design_scores_gemma":[0.00008423737,0.00001235524,0.00001145629,0.000002745802,5.591133e-7,6.898663e-7,0.02837058,0.00003862679,0.00001038005,0.001182203,0.9702371,0.00004911087],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09452525,0.0000459404,0.000009628854,0.0003955996,0.000253669,0.00002632601,0.000001142537,0.00007580416,0.9046667],"genre_scores_gemma":[0.7317157,8.236891e-7,0.00007954504,0.0004737487,0.0003390246,0.000002068756,0.000001967884,0.000003087292,0.267384],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7491769,"threshold_uncertainty_score":0.9999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1193169495235915,"score_gpt":0.2290271975789064,"score_spread":0.1097102480553149,"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."}}