{"id":"W1582883792","doi":"10.3233/fi-2013-830","title":"Sufficiently Near Neighbourhoods of Points in Flow Graphs. A Near Set Approach","year":2013,"lang":"en","type":"article","venue":"Fundamenta Informaticae","topic":"Digital Image Processing Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"H2020 European Research Council","keywords":"Mathematics; Extension (predicate logic); Flow (mathematics); Graph; Set (abstract data type); Combinatorics; Discrete mathematics; Computer science; 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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004092272,0.0002155147,0.0003017969,0.0002314127,0.00009119703,0.001441451,0.001372918,0.00007655261,0.00008966199],"category_scores_gemma":[0.00008174383,0.0001928181,0.00008570898,0.0009523033,0.0002561051,0.004491977,0.0006375791,0.0001923621,0.0002484228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006570462,"about_ca_system_score_gemma":0.0001259528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001021244,"about_ca_topic_score_gemma":0.000001215688,"domain_scores_codex":[0.9980913,0.0000346666,0.0007251611,0.0002347804,0.0004494243,0.0004646483],"domain_scores_gemma":[0.9987134,0.00005181973,0.0002406827,0.0007414513,0.0001193534,0.0001332816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004711458,0.003080235,0.02428661,0.002290232,0.0001646513,0.00001930872,0.07575471,0.000838146,0.000436867,0.09513813,0.03768798,0.7602561],"study_design_scores_gemma":[0.0006076416,0.0002306842,0.003637585,0.0001480241,0.000005201246,0.00002677849,0.0003794635,0.9745401,0.00155879,0.01632082,0.002150701,0.0003942218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2690051,0.00006177877,0.6423065,0.0006585402,0.0001773647,0.001298922,0.00002518367,0.0007207728,0.08574586],"genre_scores_gemma":[0.4791639,0.000002320859,0.5200945,0.0005814729,0.000003618651,0.0000672079,0.00001382375,0.0000100045,0.00006315809],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.973702,"threshold_uncertainty_score":0.9995952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0161775635228018,"score_gpt":0.2451965825772638,"score_spread":0.229019019054462,"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."}}