{"id":"W2152678693","doi":"10.1109/fuzzy.2006.1681723","title":"Fuzzy Object Localization Based on Directional (and Distance) Information","year":2006,"lang":"en","type":"article","venue":"","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Euclidean distance; Raster graphics; Computer science; Fuzzy logic; Object (grammar); Point (geometry); Artificial intelligence; Computation; Template; Spatial analysis; Object-based spatial database; Line (geometry); Space (punctuation); Computer vision; Euclidean space; Algorithm; Mathematics; Spatial database; Geometry","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":[0.0000764884,0.00006201069,0.00004429138,0.0001144481,0.0001175784,0.0001521117,0.00005291307,0.00002999353,0.00004513357],"category_scores_gemma":[0.00001537883,0.0000566923,0.00001652316,0.0002317693,0.00002012721,0.0007678744,0.00001154193,0.00003313302,0.00002689211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003914635,"about_ca_system_score_gemma":0.00003146841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005160169,"about_ca_topic_score_gemma":0.00005484348,"domain_scores_codex":[0.9994926,0.0000190335,0.0001362878,0.0001074419,0.0001701366,0.00007449645],"domain_scores_gemma":[0.9997258,0.00003676394,0.00004618226,0.0001047671,0.00006118695,0.00002528305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001186462,0.00003568903,0.01104449,0.00001002122,0.000002450129,4.872443e-7,0.00005837861,0.2708133,0.00001867998,0.624071,0.003030083,0.09090354],"study_design_scores_gemma":[0.0002836718,0.00002215905,0.03729102,0.000006399308,0.000001248926,0.000002492945,0.000006025498,0.9504523,0.0002290073,0.002624132,0.008990117,0.00009137863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001688909,0.00000287794,0.9164273,0.0005533488,0.0001487266,0.00007260839,0.000001645984,0.0001734677,0.08245119],"genre_scores_gemma":[0.9729437,0.000002628101,0.02592223,0.0008417043,0.00002617287,0.000006426393,0.00003754474,0.000002100836,0.0002174615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9727749,"threshold_uncertainty_score":0.2311845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003537221414437068,"score_gpt":0.1874729501177763,"score_spread":0.1839357287033392,"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."}}