{"id":"W2053173245","doi":"10.1002/net.21531","title":"Minisum multipurpose trip location problem on trees","year":2013,"lang":"en","type":"article","venue":"Networks","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Facility location problem; Type (biology); Computer science; Node (physics); Type of service; Service (business); Tree (set theory); Mathematical optimization; Flow network; Transportation theory; 1-center problem; Fixed cost; Operations research; Mathematics; Combinatorics; Engineering; Business","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":[0.0008394347,0.0009099377,0.001544147,0.001148056,0.001086242,0.001787565,0.002052878,0.001952575,0.009963757],"category_scores_gemma":[0.0027776,0.0006665342,0.0008278002,0.002928399,0.0006517174,0.00324728,0.001860526,0.0009574075,0.001154242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001341025,"about_ca_system_score_gemma":0.0005855073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002942733,"about_ca_topic_score_gemma":0.003108636,"domain_scores_codex":[0.9992954,0.000259782,0.00004252901,0.0001376958,0.0000999156,0.0001646409],"domain_scores_gemma":[0.9986709,0.0008133791,0.0001418043,0.0001046001,0.0001203437,0.0001489516],"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":[0.0006019589,0.0002901963,0.001367333,0.0007104243,0.0001144501,0.0006120903,0.0002339507,0.8041366,0.002823771,0.08999597,0.02337093,0.07574233],"study_design_scores_gemma":[0.00007264703,0.0001120004,0.000601155,0.00004693237,0.00003459909,0.0003706368,0.0002331532,0.9083505,0.001122533,0.08187937,0.007151907,0.00002450457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3124084,0.002859341,0.6406591,0.002881388,0.0002961239,0.0004737539,0.004306878,0.0006520876,0.03546293],"genre_scores_gemma":[0.8071154,0.001455211,0.1646266,0.000330255,0.0002271402,0.0003554335,0.002886701,0.0001847417,0.02281844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009963757,"threshold_uncertainty_score":0.03333205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01796952139596357,"score_gpt":0.2092997124606246,"score_spread":0.1913301910646611,"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."}}