{"id":"W4413751440","doi":"10.1145/3760214","title":"Why AI Cannot Learn South Asian Cities","year":2025,"lang":"en","type":"article","venue":"interactions","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"South asia; Computer science; History; Ancient history","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":[0.002087528,0.0004290444,0.0003327943,0.0005258464,0.007843708,0.006208072,0.0006898515,0.001795665,0.06341395],"category_scores_gemma":[0.003322246,0.0002828109,0.0003604584,0.00121571,0.006743795,0.01002256,0.005482812,0.007815138,0.0111913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004633429,"about_ca_system_score_gemma":0.006372332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06336257,"about_ca_topic_score_gemma":0.1044397,"domain_scores_codex":[0.9988903,0.0003791806,0.00003645951,0.0001215278,0.0001468532,0.000425664],"domain_scores_gemma":[0.9976748,0.0004404768,0.0001497764,0.0002111014,0.000562608,0.0009613562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001551753,0.0001590988,0.01346501,0.000628333,0.00006280637,0.001537854,0.07793903,0.0002599125,0.0009365993,0.2200952,0.5894675,0.09529338],"study_design_scores_gemma":[0.00002443656,0.00004173315,0.006497775,0.0004817396,0.00001863477,0.0002723353,0.07747575,0.0001576616,0.0003072663,0.02424208,0.8904458,0.00003478735],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04379978,0.005131585,0.0009152188,0.4433828,0.002988799,0.00004282112,0.0004838727,0.0001875029,0.5030677],"genre_scores_gemma":[0.5096532,0.01037842,0.001121895,0.1094284,0.0008004526,0.000104878,0.0003857407,0.0003595029,0.3677675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06341395,"threshold_uncertainty_score":0.2121408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102810375945805,"score_gpt":0.2400530766967854,"score_spread":0.229772039102205,"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."}}