{"id":"W2186428975","doi":"10.2298/fil1613411p","title":"Convex sets in proximal relator spaces","year":2016,"lang":"en","type":"article","venue":"Filomat","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Mathematics; Regular polygon; Normed vector space; Space (punctuation); Convex set; Combinatorics; Pure mathematics; Basis (linear algebra); Geometry; Convex optimization","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009949137,0.00004851972,0.00007231279,0.00008311219,0.0000272697,0.00004664708,0.0002079188,0.00002880772,0.0003390434],"category_scores_gemma":[0.00004479715,0.00003102333,0.00002563361,0.0002567902,0.00001123146,0.0003432003,0.00006345291,0.00002225084,0.0003883284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002308571,"about_ca_system_score_gemma":0.00002803053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005903552,"about_ca_topic_score_gemma":0.000006417831,"domain_scores_codex":[0.9994762,0.00002833394,0.0001086691,0.0001588033,0.0001291115,0.0000988743],"domain_scores_gemma":[0.999672,0.00005173175,0.00004030884,0.0001650427,0.00003413599,0.00003677781],"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":[0.00001103958,0.0001399262,0.08455831,0.000011721,0.00004007277,0.00002396644,0.0007992591,0.000366054,0.001031502,0.8918332,0.008915791,0.01226911],"study_design_scores_gemma":[0.002670867,0.0001198599,0.3653407,0.0001138507,0.00001603734,0.00002351669,0.0000365706,0.5489316,0.003191369,0.04203074,0.03679372,0.0007311822],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1259196,0.00006918875,0.8006151,0.05423111,0.0004701322,0.000269764,0.00001566061,0.0003766574,0.01803282],"genre_scores_gemma":[0.9672204,0.000007646211,0.03040889,0.0003265312,0.00002066947,0.000008909521,0.000001827307,0.000003305801,0.002001811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8498025,"threshold_uncertainty_score":0.4991305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01085814465577504,"score_gpt":0.2303135840249992,"score_spread":0.2194554393692242,"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."}}