{"id":"W2035432485","doi":"10.1111/j.1538-4632.2001.tb00434.x","title":"An Approximation for the Rank Adjacency Statistic for Spatial Clustering with Sparse Data","year":2001,"lang":"en","type":"article","venue":"Geographical Analysis","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Statistic; Adjacency list; Cluster analysis; Mathematics; Rank (graph theory); Statistics; Combinatorics","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":[0.0005538161,0.0001634665,0.0004067481,0.000245267,0.0001974828,0.00005973685,0.0003747402,0.00005176339,0.0001299728],"category_scores_gemma":[0.0002504122,0.0001019567,0.0001964487,0.001211427,0.0001298459,0.000160678,0.00006619484,0.00009108998,0.000002944042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001265875,"about_ca_system_score_gemma":0.00003903769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005051617,"about_ca_topic_score_gemma":0.005613337,"domain_scores_codex":[0.9984464,0.00005610712,0.0003020321,0.0005560401,0.0003293141,0.0003100891],"domain_scores_gemma":[0.9977349,0.0003406129,0.0001255955,0.00141401,0.0002014972,0.0001833867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00890937,0.001176264,0.7109175,0.0005553991,0.009214572,0.00005516789,0.0001522679,0.009019911,0.0002081497,0.0005177762,0.001465214,0.2578084],"study_design_scores_gemma":[0.001743673,0.0002633363,0.2651232,0.00001692628,0.006484935,0.00000746729,0.00005464545,0.7220857,0.000003126541,0.0001852627,0.003880189,0.0001514482],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04329025,0.0001487177,0.9523067,0.0009349033,0.00003272052,0.0009903549,0.002185531,0.00008071381,0.00003007646],"genre_scores_gemma":[0.9608384,0.0001495524,0.02623761,0.0002553123,0.0001918034,0.0002245028,0.01204946,0.00002297796,0.00003038732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9260691,"threshold_uncertainty_score":0.4157673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03476071642325056,"score_gpt":0.3129041771502327,"score_spread":0.2781434607269821,"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."}}