{"id":"W4391050702","doi":"10.58445/rars.903","title":"Comparison of Classification Regions for AI Geolocation","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Geolocation; Artificial intelligence; Computer science; Cartography; Geography; World Wide Web","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":[0.01143721,0.001307692,0.001395469,0.01073398,0.0009228961,0.004317809,0.002095145,0.001656619,0.009578687],"category_scores_gemma":[0.05253926,0.0002528276,0.001740819,0.007556408,0.001077303,0.004563507,0.001962903,0.001591321,0.005221723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002832042,"about_ca_system_score_gemma":0.001515138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01351473,"about_ca_topic_score_gemma":0.007902868,"domain_scores_codex":[0.9923558,0.003449696,0.0005536964,0.001237287,0.001720016,0.0006834128],"domain_scores_gemma":[0.9451004,0.04014474,0.002133236,0.00437041,0.007180278,0.00107099],"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":[0.005715794,0.0004403056,0.07750376,0.001624538,0.0009283716,0.0001943778,0.001633863,0.08072843,0.003197517,0.02620929,0.05499515,0.7468286],"study_design_scores_gemma":[0.0008064226,0.002308676,0.2106804,0.0009174726,0.001158209,0.001191837,0.009577044,0.5980672,0.0121158,0.07895599,0.08388907,0.0003318819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4747212,0.03908654,0.3311688,0.006927321,0.002271006,0.0011996,0.03210874,0.0145853,0.09793145],"genre_scores_gemma":[0.8864127,0.003029671,0.08331754,0.0003876686,0.0003761145,0.0004009445,0.02125741,0.0008602116,0.003957864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01351473,"threshold_uncertainty_score":0.06048644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1676848008200394,"score_gpt":0.4583709735192654,"score_spread":0.290686172699226,"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."}}