{"id":"W2040199445","doi":"10.1007/s101090050024","title":"Using GIS to promote spatial analysis","year":2000,"lang":"en","type":"article","venue":"Journal of Geographical Systems","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Geographic information system; Exploratory analysis; Spatial analysis; GIS applications; Data science; Geography; Software; Regional science; Environmental planning; Computer science; Cartography; Remote sensing","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":[0.003115572,0.0001594989,0.0006700282,0.001274234,0.0006494973,0.0002549262,0.0004081247,0.0001601956,0.0003436338],"category_scores_gemma":[0.0001516211,0.0001293544,0.0006259684,0.004242383,0.0001825892,0.0003651511,0.00002777596,0.0002312321,0.00004356388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008314709,"about_ca_system_score_gemma":0.00008960762,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01663015,"about_ca_topic_score_gemma":0.001637637,"domain_scores_codex":[0.9964044,0.0003301779,0.001221312,0.0001541333,0.001435307,0.0004546572],"domain_scores_gemma":[0.9979244,0.00008594329,0.0005789897,0.0002004231,0.0007890291,0.0004212265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003266035,0.0004092866,0.863694,0.0001479393,0.008344927,0.0001113952,0.05509578,0.02903159,0.0001917982,0.008686321,0.002059912,0.03190053],"study_design_scores_gemma":[0.001356183,0.0006299987,0.1919697,0.0004866345,0.002164141,0.0001489201,0.01771378,0.003325071,0.00001192021,0.0005714429,0.7806556,0.0009665902],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809237,0.0004447799,0.004677008,0.0009763208,0.0009503815,0.0004626508,0.000009964838,0.00004271894,0.01151246],"genre_scores_gemma":[0.9981526,0.00009268944,0.0005213121,0.00008066797,0.0007911047,0.000005923519,7.178331e-7,0.000008234819,0.0003467641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7785957,"threshold_uncertainty_score":0.9899182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02974681211074457,"score_gpt":0.3174409251108444,"score_spread":0.2876941130000998,"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."}}