{"id":"W4366830082","doi":"10.1111/tgis.13045","title":"The challenges of integrating explainable artificial intelligence into <scp>GeoAI</scp>","year":2023,"lang":"en","type":"article","venue":"Transactions in GIS","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; TD Bank Group","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Geospatial analysis; Scope (computer science); Computer science; Data science; Artificial intelligence; Artificial neural network; Semantics (computer science); Geography; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01106977,0.0005728995,0.0006984383,0.001861303,0.001192811,0.005981288,0.002055156,0.002053305,0.004212008],"category_scores_gemma":[0.03456191,0.0006129789,0.001000554,0.002711761,0.007226176,0.01043614,0.005354726,0.005084066,0.0006602008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003088,"about_ca_system_score_gemma":0.002832625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01377454,"about_ca_topic_score_gemma":0.01005593,"domain_scores_codex":[0.9944658,0.003338623,0.0003192796,0.0006439155,0.001027803,0.0002046365],"domain_scores_gemma":[0.969716,0.02093383,0.001789378,0.00498664,0.00212804,0.0004460578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002121341,0.00004562696,0.004882941,0.0001992039,0.0001101254,0.0002617058,0.0005365928,0.07013696,0.0004911675,0.8447554,0.006892436,0.07166665],"study_design_scores_gemma":[0.000003813073,0.000006531912,0.0006515569,0.00007552302,0.00001082583,0.00005733026,0.000251543,0.1726876,0.0004066611,0.8158733,0.009960796,0.00001466694],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02266597,0.001329412,0.9042787,0.05319234,0.0001975493,0.00008660921,0.0007218815,0.0008262749,0.01670126],"genre_scores_gemma":[0.654214,0.001879986,0.3359001,0.003139414,0.0004555845,0.0001656673,0.0008515405,0.0003319903,0.003061777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01377454,"threshold_uncertainty_score":0.05854326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0625456185125108,"score_gpt":0.2967160792416709,"score_spread":0.2341704607291601,"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."}}