{"id":"W4417148218","doi":"10.1007/s10109-025-00485-0","title":"Supervised spatial metric learning with applications to spatial clustering and spatial model prediction","year":2025,"lang":"en","type":"article","venue":"Journal of Geographical Systems","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Mitacs; Compute Canada","keywords":"Similarity (geometry); Cluster analysis; Random forest; Spatial analysis; Metric (unit); Pattern recognition (psychology); Inference; Data modeling","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":[0.004979732,0.001157498,0.002527271,0.00292258,0.001225862,0.001700527,0.003070134,0.002058676,0.002132126],"category_scores_gemma":[0.02644967,0.0009221982,0.001563383,0.003966561,0.001469564,0.002886357,0.003308063,0.002936063,0.0007061465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001605888,"about_ca_system_score_gemma":0.002431279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01527957,"about_ca_topic_score_gemma":0.01854564,"domain_scores_codex":[0.9970505,0.001615393,0.0002163417,0.0005635871,0.0004546224,0.00009955528],"domain_scores_gemma":[0.9787093,0.01491367,0.0009771942,0.002308507,0.002654977,0.0004362537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001201946,0.0002701911,0.003909708,0.000172706,0.0002188226,0.00007700607,0.0001786307,0.7322424,0.0006017998,0.03342727,0.008484877,0.2202964],"study_design_scores_gemma":[0.000004633001,0.000008155775,0.0001186274,0.000003221323,0.000004220407,0.00000654531,0.000008776561,0.9834728,0.00008299373,0.01599121,0.0002949021,0.000003844899],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01395098,0.0006246637,0.9830757,0.0005296777,0.00007576591,0.00005019302,0.0003043682,0.0008441638,0.0005444154],"genre_scores_gemma":[0.3784884,0.0008404572,0.6139022,0.0002509705,0.0003516904,0.0003234258,0.00243075,0.0003521349,0.003059899],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01527957,"threshold_uncertainty_score":0.03038126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772213330354659,"score_gpt":0.2167169210232245,"score_spread":0.1989947877196779,"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."}}