{"id":"W1599294059","doi":"10.1007/978-3-540-68825-9_8","title":"Use of Fuzzy Histograms to Model the Spatial Distribution of Objects in Case-Based Reasoning","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Jaccard index; Histogram; Artificial intelligence; Representation (politics); Partition (number theory); Fuzzy logic; Granularity; Pattern recognition (psychology); Image (mathematics); Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002025588,0.0004805053,0.0007129823,0.001811718,0.0004368472,0.002081499,0.001975259,0.000849274,0.003110236],"category_scores_gemma":[0.007862336,0.000595245,0.0008412216,0.002186087,0.00114852,0.003807781,0.001096209,0.001038011,0.0004162488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001266647,"about_ca_system_score_gemma":0.0007790242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0143773,"about_ca_topic_score_gemma":0.01032732,"domain_scores_codex":[0.9992678,0.0002440616,0.00006942065,0.0001186793,0.0002485805,0.00005147253],"domain_scores_gemma":[0.9967855,0.002151783,0.0001936486,0.0004188083,0.0003420434,0.0001080614],"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":[0.0002416174,0.0001747826,0.002573318,0.0001364708,0.0001181466,0.0002705666,0.0004719216,0.544786,0.003627567,0.1454716,0.002447481,0.2996805],"study_design_scores_gemma":[0.00001604845,0.00001642162,0.0003243641,0.00001313473,0.00002298026,0.00007726314,0.00003582846,0.9349378,0.001108025,0.06217911,0.001251837,0.00001719949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008485925,0.0002035525,0.9892714,0.00008950003,0.00002431343,0.00003487939,0.0001153462,0.0005077948,0.001267205],"genre_scores_gemma":[0.3840719,0.0004013444,0.6133435,0.00006153918,0.00003743733,0.0001170097,0.0003038551,0.0001086292,0.001554655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0143773,"threshold_uncertainty_score":0.02858722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03098571319675893,"score_gpt":0.2376545933230285,"score_spread":0.2066688801262695,"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."}}