{"id":"W1987170162","doi":"10.1016/j.engappai.2014.04.004","title":"FIA5: A customized Fuzzy Interval Algebra for modeling spatial relevancy in urban context-aware systems","year":2014,"lang":"en","type":"article","venue":"Engineering Applications of Artificial Intelligence","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Context (archaeology); Fuzzy logic; Interval (graph theory); Theoretical computer science; Artificial intelligence; Algebra over a field; Data mining; 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":[0.001114475,0.000718714,0.0007482928,0.001045209,0.0006629868,0.001780412,0.002127582,0.0007704022,0.004054266],"category_scores_gemma":[0.002633398,0.0003185096,0.001600313,0.0012376,0.0004821164,0.002011857,0.001066066,0.001326133,0.0008685875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00091987,"about_ca_system_score_gemma":0.001383644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01182078,"about_ca_topic_score_gemma":0.01264282,"domain_scores_codex":[0.9992635,0.0001501457,0.00007451873,0.0001722303,0.0002717466,0.00006783364],"domain_scores_gemma":[0.9994406,0.0001488422,0.00006434836,0.0001357152,0.0001630373,0.00004750777],"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":[0.0001898362,0.0001588017,0.00232699,0.0002450729,0.0001556639,0.0002890031,0.0003585854,0.6189576,0.009965327,0.2204223,0.007723212,0.1392076],"study_design_scores_gemma":[0.00001053252,0.00003112408,0.0002361183,0.00001573658,0.00002632493,0.00005976413,0.00003227663,0.9491174,0.002052539,0.03812737,0.01027046,0.00002030341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006328368,0.0001329044,0.9890817,0.00005167076,0.00004896318,0.00005596081,0.0006286532,0.001143854,0.002527861],"genre_scores_gemma":[0.3382671,0.0003133551,0.655249,0.0001176552,0.00008547735,0.0002410219,0.001837555,0.0002147053,0.003674003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01182078,"threshold_uncertainty_score":0.02350396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02274273637091325,"score_gpt":0.2532920496401176,"score_spread":0.2305493132692044,"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."}}